14971 results for "cancer studies using rna-seq"

in 20.44 milliseconds.

• CD4 T-Cell RNA-Seq

  CD4 T-Cell RNA-Seq

  Dataset EGAD00001002687

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Study EGAS00001004516

• RNA-seq

  RNA-seq data

  Dataset EGAD00001008959

• LGG Epilepsy Cohort RNA-Seq

  LGG Epilepsy Cohort RNA-Seq

  Dataset EGAD00001001666

• RNA-seq iNKT, T and C1R cells

  RNA-seq (Ribodepleted Directional -75 PE- Hiseq 4000) data of purified and expanded iNKt and T cells from normal donor, and RNA-seq (poly-A 100-PE Hiseq 2500) data from C1R cell line. Data set consist of 3 pairs of fastq files, one pair per sample

  Dataset EGAD00001004331

• Short-read (RNA-seq)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006596

• Analyses of RNAseq data from NEN patient derived tumor organoids (PDTOs) and matched parental tumors

  The dataset includes RNA-seq expression R data, RNA-seq gene counts matrix, and RNA-seq gene FPKM matrix from 21 NEN tumors or metastases and matched PDTOs. The sequencing was done with either a Nextseq 2000 or a NovaSeq 6000 instrument.

  Dataset EGAD00001009994

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  This dataset consists of RNA-seq CRAM raw-data files of 1063 primary colorectal cancer and 120 adjacent normal tissue samples. The expression profiles for these samples can be found at the ArrayExpress with accession number E-MTAB-12862.

  Dataset EGAD50000000169

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441

• Chip_seq_oesophageal_adenocarcinoma_

  There is complex interplay between underlying genetic sequence and epigenetic factors, however this interplay is still illusive. Massively reconstructed cancer genomes can be used in order to better understand this relationship. Six oesophageal adenocarcinoma organoids will be sequenced using long read sequencing technologies and will be profiled for a range of epigenetic marks. Combination of genetic and epigenetic data will allow the thorough characterisation of reference cancer genomes and will provide novel insights into mechanisms of gene regulation. Description: Chip-seq Sequencing of 5 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger.

  Study EGAS00001007180

• Integration of human pancreatic islet genomic data refines regulatory mechanisms at Type 2 Diabetes susceptibility loci

  Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n=17) and DNA methylation (whole-genome bisulphite sequencing, n=10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis.

  Study EGAS00001002592

• RNA-seq from B-ALL patients treated on the ALLG ALL09 study

  Dataset contains RNA-sequencing data (fastq files) from 46 patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL09 study (ACTRN12618001734257). All patients were diagnosed with CD19 positive B-cell acute lymphoblastic leukaemia and were negative for Philadelphia chromosome positive disease. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from lymphoblasts and underwent paired-end sequencing using either the illumina NextSeq (75 bp PE) or MGI DNABSEQ-G400 (100bp PE) platforms. Transcriptomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).

  Dataset EGAD50000001603

• Bulk RNA-sequencing datasets from Caco-2 cells under normal or inflamed conditions treated with 4HTBZ or vehicle.

  This dataset contains 4 bulk RNA sequencing files (.fastq.gz) and a metadata file (.csv) from Caco-2/TC7 intestinal epithelial cells under normal or inflamed conditions, followed by treatment with 4HTBZ or vehicle. The cDNA libraries were prepared with the QuantSeq 3′ mRNA-Seq Kit (Lexogen, Inc.) and sequenced on an Illumina HiSeq4000 system. The metadata file provides sample information (experimental condition and code identifier). Raw sequencing reads were quality-checked with FastQC, trimmed with Trimmomatic, and aligned to the human reference genome (GRCh38) using HISAT2.

  Dataset EGAD50000001759

• RNA-seq Phase Ib of olaparib and capivasertib

  RNA-seq Phase Ib of olaparib and capivasertib

  Dataset EGAD00001006840

• RNA-seq from normal human tissues

  RNA-seq from normal human tissues (2 x 75 bp)

  Dataset EGAD00001001057

• RNA-seq from normal human tissues

  RNA-seq from normal human tissues (2 x 250 bp)

  Dataset EGAD00001001922

• RNA-seq from melanoma biopsies

  RNA-seq data for melanoma biopsies at baseline and after treatment

  Dataset EGAD00001009059

• Lactobacillus rhamnosus GG ATCC (LGG) as an immune adjuvant for influenza vaccination in the elderly

  Double blind Randomized Controlled trial to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) vs placebo in elderly receiving Trivalent Inactivated Influenza Vaccine (TIV) (study 1) or Double blind Randomized Controlled trial to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) vs. placebo in elderly subjects receiving Live Attenuated Influenza vaccine (LAIV) (study 2). Healthy elderly volunteers, ages 65-80 were enrolled as outpatients in two clinical studies in which they received the TIV vaccine (study 1, n=28) or the LAIV vaccine (study 2, n=30). In each of the 2 studies, subjects were randomized to receive either LGG capsules containing 1 x 1010 CFU, twice daily for 28 days, or matching placebo capsules twice daily for the same period of time. The study subjects completed a daily diary, telephone calls, and study visits at the Massachusetts General Hospital Clinical Research Centers at baseline, days 21, 28 and 56 and month 5 for the TIV study and baseline, days 21, 28, and 56 for the LAIV study. During each visit, the subject diary, interim history, potential adverse effects and concomitant medications were reviewed and vital signs and a physical examination were performed. Routine blood tests were obtained to monitor for safety during visits and nasopharyngeal and stool samples were collected for microbiome analysis. Volunteers in both studies who were interested in participating in the effect of LGG probiotic on the Human whole Blood Transcriptome substudy also had blood drawn for DNA and RNA extraction, after signing the substudy consent form. The main objectives of the TIV and LAIV studies were to assess the safety and tolerability of 2 x 1010 CFU LGG administered orally to elderly subjects for 28 days after administration of TIV (study 1) or LAIV (study 2). Secondary objectives were to evaluate the richness and microbial diversity in nasopharyngeal and stool specimens using pyrosequencing, and to compare cytokine production in response to bacterial stimulation by following the kinetics of mRNA expression of pro and anti-inflammatory genes and different signaling pathways, in relation to changes in stool Bifidobacterium and Lactobacillus spp. The studies were reviewed and approved by the Partners Human Research Committee (TIV study IRB # 2010p001694 and LAIV study IRB # 2011p002849) and were registered at ClinicalTrials.gov (NCT01368029 and NCT01545349, respectively).

  Study phs000981

• Immune Determinants of Resistance to PD-1 Blockade in Renal Cell Carcinoma

  We performed an integrated bulk and single-cell transcriptomic analysis of tumors from 102 advanced renal cell carcinoma patients enrolled in a phase II clinical trial of frontline nivolumab (NCT03117309) to investigate determinants of response to anti-PD1 monotherapy. The present study includes 112 archival or pre-treatment tumors of clear cell and non-clear cell histologies from 90 patients that underwent bulk RNA sequencing (RNA-seq). For 76 patients, 74 of whom had matched RNA-seq, whole exome sequencing (WES) was also performed on tumor samples as well as matched peripheral blood. Additionally, 19 fresh tumor samples from 17 patients, including pre and post-treatment samples and mixed histologies, were locally cryopreserved and centrally processed for single cell RNA (scRNA-seq) and TCR (scTCR-seq) sequencing. 7 patients had matched scRNA/scTCRseq, RNAseq, and WES.

  Study phs003618

• Evaluation of Local Response of Prostate Cancer to Irradiation Using Multiparametric MRI and MR-Guided Biopsies

  The purpose of this study was to determine the rate of local recurrence in patients with intermediate and high risk prostate cancer treated with radiotherapy. In this study, multiparametric MRI was first performed, and biopsy tissue was acquired from cancerous regions detected on MRI. Blood samples were also taken. DNA and RNA were extracted from tissue taken at baseline. DNA was used for whole exome sequencing (WES). RNA was used for gene expression microarray. Each patient then received radiation therapy with androgen deprivation therapy.

  Study phs001821

• Systemic Inflammation and Lymphocyte Activation Precede Rheumatoid Arthritis

  The Allen Institute for Immunology-University of California, San Diego-University of Colorado Transition to Rheumatoid Arthritis (ALTRA) project is a prospective longitudinal cohort study to understand the pre-clinical development of rheumatoid arthritis (RA). We performed cross-sectional and longitudinal multi-omics analyses of peripheral immunity in the anti-citrullinated protein autoantibody-positive (ACPA+) at-risk for RA period. We provide FASTQ files from (1) single-cell RNA sequencing (scRNA-seq) of ACPA+ at-risk (n=45), ACPA+ early RA (n=11), and site-matched ACPA- controls (n=38); (2) scRNA-seq of longitudinal samples from ACPA+ at-risk who developed clinically active RA during our study (n=16 participants, n=75 samples) and ACPA- controls (n=29 subjects, n=89 samples); (3) trimodal TEA-seq of a subset of ACPA+ at-risk (n=7) and ACPA- controls (n=5). Using these data, we characterize pathogenesis prior to clinical RA diagnosis and suggest the at-risk state exhibits substantial immune alterations that could potentially be targeted for early intervention to delay or prevent autoimmunity.

  Study phs003944

• Methylation biomarker study of magnesium deficiency and colorectal cancer

  Five US studies using the Mg tolerance test, the "gold standard" test of Mg status, indicated that >50% participants had Mg deficiency. In our ongoing US trial, we have found a similar result. In growing recognition of the importance of Mg in human health, very recently, Mg was selected by the US Federal Dietary Reference Intake (DRI) Committee to update the DRI. In US and other populations at high risk of Mg deficiency, high Mg intake has been linked to reduced risk of colorectal neoplasia, insulin resistance, metabolic syndrome, type 2 diabetes, and cardiovascular disease (CVD). Conversely, in populations not at high risk of Mg deficiency, high Mg intake has been related to increased risk of total mortality (e.g. total cancer, colorectal cancer, and CVD), particularly when calcium intake is low. These observations suggest that the associations between high Mg intake and disease risks may completely differ by the underlying Mg status. Due to major limitations, the Mg tolerance test is not used in conventional clinical practice and rarely used in research. Instead, serum Mg is used for clinical diagnosis. However, serum Mg performs very poorly at identifying those with Mg deficiency. There is a great need to develop implementable, sensitive, and specific biomarkers which can be easily used for identifying people with Mg deficiency. Without such a marker, it is impossible to develop effective strategies that minimize adverse effects by targeting those who, as a result of Mg deficiency, are at risk of common diseases. It is known that DNA methylation changes are inducible by environmental exposures, including nutrients, and reversible when the exposure disappears. There are two major types of cytosine modifications in DNA, 5-hydroxymethylcytosine (5-hmC) and 5-methylcytosine (5-mC). 5-mC is often associated with suppressed gene expression. 5-hmC, generated by the oxidation of 5-mC, is specifically enriched in expressed genes and plays a critical role in activating and/or maintaining gene expression. However, current epigenomic profiling platforms cannot distinguish 5-hmC from 5-mC. Just recently, our collaborator, Dr. Chuan He (HHMI Investigator), established a novel and state of the art technique, TAB-Seq and TAB-Array protocol, which can separate 5-hmC from 5-mC in the genome. Our pilot studies indicate that Mg intake or treatment significantly affects methylation capacity, 5-mC and 5-hmC biomarkers. Our findings suggest blood leukocyte 5-hmC/5-mC biomarkers may serve as more sensitive biomarkers to identify Mg deficiency than serum Mg. Thus, a comprehensive epigenome-wide association study (EWAS) may help to identify the most sensitive 5-hmC/ 5- mC biomarkers for Mg deficiency. We propose to identify 5-hmC/5-mC biomarkers for Mg deficiency by a 4- phase EWAS study in the "Personalized Prevention of Colorectal Cancer Trial [PPCCT, R01CA149633; PI, Dai and Yu]" with a total of 240 participants. Mg tolerance test will be used as the gold standard. Finally, using newly identified biomarkers, we will evaluate if 12-week Mg treatment reduces TRPM7 expression, essential in Mg homeostasis and colorectal carcinogenesis, in rectal tissues only among those with Mg deficiency.

  Study phs002037

• Epigenomic dataset of Human Hepatocellular Carcinoma for EpiHK

  This dataset is generated for EpiHK. It contains Histone PTM ChIP-seq, WGBS, RNA-seq of Human Hepatocellular Carcinoma and tumor adjacent normal tissue sample.

  Study EGAS50000000039

• High-Throughput RNA Isoform Sequencing using Programmable cDNA Concatenation

  MAS-ISO-seq is a novel technique for programmably concatenating cDNAs into single molecules for optimal long-read sequencing. In practice, this boosts throughput >15 fold to nearly 40 million cDNA reads per run on the PacBio Sequel IIe sequencer. We have validated this method via application to synthetic RNA isoforms and single-cell sequencing of tumor-infiltrating T cells. Results demonstrated a >30 fold boosted discovery of differentially spliced genes and robust cell clustering, as well as canonical PTPRC splicing patterns across T cell subpopulations and the concerted expression of the associated hnRNPLL splicing factor.

  Study phs003200

• Genome-wide association study for Bladder Cancer Risk

  This study funded by the National Cancer Institute (NCI) involves conducting a genome-wide association study of common genetic variants to identify markers of susceptibility to bladder cancer. This bladder GWAS has led to the discovery of three novel regions in the genome associated with bladder cancer risk. Cases were defined as individuals having histologically confirmed primary carcinoma of the urinary bladder, including carcinoma in situ (ICD-0-2 topography codes C67.0-C67.9 or ICD9 codes 188.1-188.9). Scan data were obtained from two case-control studies carried out in Spain and the United States (specifically, those in the Maine and Vermont components of the New England Bladder Cancer Study) and three prospective cohort studies in Finland and the United States (specifically Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study, Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, and The American Cancer Society Cancer Prevention Study II Nutrition Cohort). We used data from 591,637 single nucleotide polymorphisms 3,532 affected individuals (cases) and 5,119 controls of European descent and replication including 8382 cases and 48275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P ≈ 8 x 10-12) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 x 10-11) on maps to CCNE1 and rs11892031 (P = 1 x 10-7) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3 (Rothman N et al., Nature Genetics, 2010, PMID: 20972438). Through meta-analysis with the MD Anderson Texas Bladder Cancer Study (TXBCS), we also identified a novel susceptibility locus that mapped to a region of 18q12.3, marked by rs7238033 (P = 8.7 x 10(-9); allelic odds ratio 1.20 with 95% CI: 1.13-1.28) and two highly correlated SNPs, rs10775480/rs10853535 (r(2)= 1.00; P = 8.9 x 10(-9); allelic odds ratio 1.16 with 95% CI: 1.10-1.22) (Garcia-Closas M et al, Human Molecular Genetics, 2011) For NCI-GWAS2, we performed genotyping on cases and controls for the New Hampshire component of the New England Bladder Cancer Study (NEBCS-NH). For the majority of new bladder cancer cases, we genotyped only cases from four case-control studies, the Los Angeles Bladder Cancer Study (LABCS), the French Center for Research on Prostate Diseases (CeRePP), the French Bladder Study (FBCS) and the Brescia Bladder Cancer Study (BBCS). We used existing control data from four cohort studies already genotyped and subjected to rigorous quality control metrics: the European Prospective Investigation Into Cancer and Nutrition Study (EPIC), Womens Health Initiative (WHI), Health Professionals Follow-up Study (HPFS), Nurses Health Study (NHS), which have been a part of Cancer Genetic Markers of Susceptibility (CGEMS). Meta-analysis of NCI-GWAS1, NCI-GWAS2 and a previously reported GWAS TXBCS-GWAS along with taqman replication, identified two new loci: rs10936599 on 3q26.2 (P = 4.53 x 10(-9)) and rs907611 on 11p15.5 (P = 4.11 x 10(-8)). Two notable loci were also identified that approached genome-wide statistical significance: rs6104690 on 20p12.2 (P = 7.13 x 10(-7)) and rs4510656 on 6p22.3 (P = 6.98 X 10(-7)); these require further studies for confirmation (Figueroa J et al, Human Molecular Genetics, 2013).

  Study phs000346

• CIDR: Molecular Pathological Epidemiology of Colorectal Cancer

  Colorectal cancer, the second most commonly diagnosed cancer is a biologically heterogeneous disease. To characterize the molecular attributes of colorectal tumors, we conducted targeted sequencing at the Center for Inherited Disease Research (CIDR) on 4,518 tumor and matched normal DNA samples from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colon Cancer Family Registry (CCFR). These consortia are based on cohort and population-based case-control studies.

  Study phs001905

• NSD2 E1099K Drives Relapse in Pediatric Acute Lymphoblastic Leukemia by Disrupting 3D Chromatin Organization

  NSD2 p.E1099K (EK) is a mutation shown to be enriched in patients that relapse with pediatric Acute Lymphoblastic Leukemia (ALL). This work aims to uncover 3D chromatin architecture-related mechanisms responsible for drug resistance or therapy failure in these patients. We investigated this by performing Hi-C, ATAC-Seq, and RNA-Seq on three B-ALL cell lines heterozygous for EK either expressing a NSD2 targeting small RNA (sRNA) or a non-targeting small hairpin RNAs (shRNA). We also performed RNA-Seq on three matched diagnosis/relapse B-ALL samples with the relapse enriched EK mutation.

  Study phs003195

• RNA seq reads

  RNA seq reads constituting of FASTQ paired end reads from 5 FHD/FHDL patients

  Dataset EGAD00001003790

• Paired-end RNA-seq analysis of GBM, additional patient.

  Dataset contains one paired-end RNA-seq sample.

  Dataset EGAD00001011990

• Exploration of coding and non-coding variants in cancer using GenomePaint.

  GenomePaint (https://proteinpaint.stjude.org/genomepaint) is a dynamic visualization platform for whole-genome, whole-exome, transcriptome, and epigenomic data, featuring a novel design that captures the inter-relatedness between DNA variations and RNA expression. Regulatory non-coding variants can be inspected and discovered along with coding variants, and their functional impact further explored by examining 3D genome and/or ChIP-seq data generated from cancer cell lines. Further, GenomePaint correlates mutation and expression patterns with patient outcomes, and can display external data such as adult cancer datasets and user-provided custom tracks. We used GenomePaint to analyze multi-omics data from 3,652 pediatric cancers representing 16 histotypes, and demonstrate the visualization features through examples, including two that led to new insights into oncogenic mechanisms in pediatric cancer. The first is the discovery of a new class of pathogenic recurrent variants that cause aberrant splicing, disrupting the RING domain of CREBBP, a driver gene frequently mutated in relapsed pediatric leukemia. The second is the cis-activation of the MYC oncogene in a subset of B-lineage acute lymphoblastic leukemia (B-ALL) via duplication of the NOTCH1-MYC enhancer (N-ME), previously discovered only in T-lineage ALL. The regulatory impact of N-ME enhancer amplification was initially confirmed by allelic imbalance in published gene expression and ChIP-seq data and verified by additional Capture-C and fluorescence in situ hybridization data generated by follow-up experiments. These examples demonstrate the power of GenomePaint in enabling not only data visualization but also integrative genomic analysis that can lead to novel biological insight for follow-up experimental validation.

  Study EGAS00001004669

• Pathogenesis and Immunity in Endemic Burkitt Lymphoma

  This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

  Study phs001282

• The landscape of chromothripsis across adult cancer types

  Chromothripsis is a recently identified mutational phenomenon, by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosome(s). Considered as an early event in tumour development, this form of genome instability plays a prominent role in tumour onset. Chromothripsis prevalence might have been underestimated when using low-resolution methods, and pan-cancer studies based on sequencing are rare. We analysed chromothripsis in 28 tumour types covering all major adult cancers (634 tumours, 316 whole-genome and 318 whole-exome sequences). We show that chromothripsis affects a substantial proportion of human cancers, with a prevalence of 49% across all cases. Chromothripsis generates entity-specific genomic alterations driving tumour development, including clinically relevant druggable fusions. Chromothripsis is linked with specific telomere patterns and univocal mutational signatures in distinct tumour entities. Longitudinal analysis of chromothriptic patterns in 24 matched tumour pairs reveals novel insights in the clonal evolution of tumours with chromothripsis. (H021)

  Study EGAS00001004250

• Transcriptomic Profiling of Bulk Tissue and Laser-Capture Microdissected Neurons of Postmortem Human Brains in the Superior Temporal Gyrus

  We performed RNA-Seq on bulk tissue and laser-capture microdissected (LCM) neurons from 59 postmortem human brains in the superior temporal gyrus (STG) to investigate Autism Spectrum Disorder (ASD)-associated transcriptomic changes. We examined post-mortem brain tissue from 27 subjects with ASD and 32 neuro-typical controls. Raw RNA-Seq data in FASTQ format are provided.

  Study phs003208

• PELICAN45 and GP21 prostate cancer studies Data Access Committee

  Dac EGAC00001001309

• WGS, RNA-seq and methyl-seq data for multiple tumour clones from a single glioblastoma case.

  10 bams of WGS data from HiSeqXTen platform; 10 bams of RNA-seq data from HiSeq2500 platform; 7 bams of TruSeq Methyl Capture EPIC sequencing data from HiSeq4000 platform

  Dataset EGAD00001004773

• Analysis of Treg gene expression patterns by RNA-Seq in patients with rheumatoid arthritis (RA) and healthy controls (HCs) : Comparison between young and elderly individuals

  We compared the gene expression of CD4+CD45RA-CD25hiCD127lo Treg cells from PBMCs between young and elderly RA patients and HCs by RNA-seq

  Study JGAS000693

• Whole genome sequencing, SNP array and RNA-seq of uveal melanomas

  We conducted whole genome sequencing and DNA SNP array of 12 uveal melanoma genomes and their matched DNA from blood. We also conducted RNA-seq of the 12 tumour samples.

  Study EGAS00001000472

• RNA-seq data from hypothalamic tissue from individuals with Prader-Willi syndrome and age-matched controls.

  RNA-seq data (bam files) from the hypothalamus of 4 individuals with Prader-Willi syndrome and 4 age-matched control individuals. Detailed information about the study design, case-control matching and RNA-seq data processing is provided in the accompanying publication [Bochukova et al (2018) Cell Reports].

  Dataset EGAD00001004034

• RNA-Seq dataset

  10 RNA-Seq bam files including 4 cases with fusion and 6 controls without fusion.

  Dataset EGAD00001004360

• RNA-Seq and WXS from 6 glioblastoma patients

  RNA-Seq and WXS from 6 glioblastoma patients

  Dataset EGAD00001003293

• Single-cell RNA-seq data of angioimmunoblastic T-cell lymphoma

  Single-cell RNA-seq data of angioimmunoblastic T-cell lymphoma

  Dataset EGAD00001011361

• IPF Core Biopsy Study RNA-Seq Fastqs

  RNA-Seq fastq files for 97 Idiopathic Pulmonary Fibrosis samples.

  Dataset EGAD00001007568

• Bulk RNA-seq osteosarcoma

  We profiled 23 patient osteosarcoma tumor samples by bulk RNA-seq. The raw fastqs are provided.

  Dataset EGAD00001011371

• RNA-Seq files for SJOS study

  RNA-Seq files for SJOS study

  Dataset EGAD00001003154

• Integrated diagnosis based on transcriptome analysis in suspected pediatric sarcomas

  We performed RNA-sequencing in 47 patients with suspected pediatric sarcomas, to evaluate the potential utility of RNA-seq in the diagnostic process of pediatric sarcoma.

  Study JGAS000284

• Whole-genome landscape of adult T-cell leukemia/lymphoma

  Whole-genome sequencing (WGS) data of tumor-normal pairs from 139 ATL patients and RNA sequencing (RNA-seq) data of tumors from 28 ATL patients.

  Study EGAS00001005237

• Melanoma Brain Metastasis Single-Cell RNA Sequencing Atlas

  Melanoma brain metastasis (MBM) frequently occurs in patients with advanced melanoma, yet our understanding of the underlying salient biology is rudimentary. Here, we performed single-cell/nucleus RNA-seq in 22 treatment-naive MBM (scRNA-seq n=5; snRNA-seq n=17) and 10 extracranial melanoma metastases (ECM; all snRNA-seq), and matched spatial single-cell transcriptomics (n=16) and T cell receptor (TCR)-seq (n=5). Key observations were validated in matched bulk RNA- and ATAC-seq of isogenic MBM/ECM cell culture models (n=24; including triplicates (labeled as *-A, -B and -C) of 4 MBM- and 4 ECM-derived patient cell lines with 2 matched pairs). This work provides comprehensive insights into MBM biology and serves as a foundational resource for further discovery and therapeutic exploration.

  Study phs002944

• Genomic Alterations in Gingivo-buccal Cancer: ICGC-India Project_YR02

  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 tumour tissue and from the blood of fifty six 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 tumour 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 tumour DNA samples using 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 70x for Tumour and 40x for Blood. In addition, we have used Illumina Omni 2.5 SNP-chips to generate genotype data.

  Study EGAS00001001028

• Identification of cardiovascular biomarkers through an integrative omics approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionally annotate index SNPs. With a large number of association signals located outside coding regions there has been an intense search among sequence variants affecting gene expression at the transcriptional level. However, little progress has been made in mapping regulatory variants that affect protein levels at the translational or post-translational level. It is now possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins by mass spectrometry. We have established a collaboration with a longitudinal, family-based study in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295 individuals) and has follow up data for 10 years (three visits). We have undertaken a pilot study 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 proteins measured in PBMCs. We have already generated GWAS data using Illumina's core-exome chip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq to generate 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/

  Dataset EGAD00001002197