12215 results for "cancer rna-seq"

in 36.29 milliseconds.

• resistance to FGFR inhibitor from RNA sequencing

  WTS performed on tissues from resistant patients

  Study EGAS50000000306

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models enables specific monitoring of tumour-derived extracellular RNA

  Study EGAS00001005740

• CGC_RNAseq

  RNA sequencing during time series

  Dataset EGAD00001006321

• RNAseq data

  Individual FASTQ files from RNA sequencing.

  Dataset EGAD00001008796

• Colorectal_organoids_and_tumoroids___pulldown

  Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient.

  Study EGAS00001000869

• Short-read scRNA-seq

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

  Dataset EGAD50000002210

• Frequent mutation of the FOXA1 untranslated region in prostate cancer

  We sequenced the coding and untranslated regions of 72 prostate cancer driver genes in 712 plasma cell free DNA samples from 428 men with metastatic prostate cancer, in an effort to understand the role of untranslated region mutations in late stage prostate cancer.

  Study EGAS00001003113

• Prevalence of rare pathogenic variants in cancer-predisposing genes among Japanese advanced prostate cancer patients.

  The prevalence of rare pathogenic variants in cancer-predisposing genes including those associated with DNA repair remains unknown among Japanese patients with advanced prostate cancer. This study was designed to elucidate the prevalence of pathogenic variants in 27 known cancer-predisposing genes and to explore the prognostic significance of the variants identified.

  Study JGAS000509

• Molecular Subtyping Reveals Immune Alterations Associated with Progression of Bronchial Premalignant Lesions

  Exposure to cigarette smoke creates a field of injury throughout the entire respiratory tract inducing genomic alterations that lead to an "at-risk" airway where lung cancers develop. Lung squamous cell carcinoma (SCC) arises in the epithelial layer of the bronchial airways and is often preceded by the development of premalignant lesions (PMLs). Effective tools to identify and treat premalignant lesions at highest risk of progression to invasive carcinoma are not available. Endobronchial biopsies and brushings were obtained from high-risk subjects undergoing lung cancer screening at approximately 1-year intervals by white light and auto-fluorescence bronchoscopy and computed tomography at the Roswell Park Cancer Institute in Buffalo, NY. Subjects were selected that had biopsies collected in repeat locations via serial bronchoscopies. mRNA sequencing was performed on a discovery cohort (DC) of samples comprising endobronchial biopsies and brushes collected between 2010 and 2012 (n=30 subjects, n=197 biopsies, and n=91 brushings). mRNA sequencing was subsequently performed on a validation cohort (VC) of samples comprising endobronchial biopsies and brushes collected between 2010 and 2015 (n=20 subjects, n=111 biopsies, and n=49 brushings). Data analysis identified four distinct molecular subtypes (Proliferative, Inflammatory, Secretory, and Normal) in the bronchial biopsies that correspond to a spectrum of biological and morphological alterations. The Proliferative subtype was enriched with dysplastic PMLs from current smokers that exhibit up-regulation of metabolic and cell cycle pathways and down-regulation of cilium-associated processes. Molecular subtype classification in the validation cohort biopsies replicated these significant clinical and biological associations. Airway brushes from normal fluorescing areas of the large airway classified as the Proliferative subtype specifically predict the presence of biopsies of this same subtype. Within the Proliferative subtype, genes associated with interferon signaling and antigen processing and presentation were observed to be down-regulated among dysplastic biopsies that persist or progress in the future. Innate and adaptive immune cells were computationally predicted to be depleted in these biopsies and this was confirmed via immunofluorescence staining of adjacent biopsies. These findings provide a proof of concept that molecular biomarkers of endobronchial biopsies can enhance histopathological grading and that immunoprevention strategies are an important future direction in intercepting the progression of PMLs to lung cancer.FASTQ files from the RNA sequencing of these biopsies and brushings will be available via dbGaP.

  Study phs003185

• Lung Cancer Genetic Study Among Asian Never Smokers

  The Lung Cancer Genetic Study Among Asian Never Smokers includes data from four population-based studies conducted among Asian women: the Shanghai Women's Health Study (SWHS), the Hwasun Cancer Epidemiology Study (HCES1 and HCES2), the Female Lung Cancer Consortium in Asia (FLCCA, including sFLCA), and the Guangzhou Lung Cancer Study (GLCS). Shanghai Women's Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Lung cancer patients identified in the SWHS and non-cases were included in the current study.Hwasun Cancer Epidemiology Study-Lung Cancer (HCES1 and HCES2): The HCES is a hospital-based case-control study whose goal is to identify factors of the cancer development and clinical progression in a Korean population. Included in this project were 299 female lung cancer cases from HCES2, who were diagnosed between April 2004 and February 2013 at Chonnam National University Hwasun Hospital, a cancer specified hospital in Jeollanam-do province, South Korea. Controls were randomly selected from women with no previous cancer diagnosis at enrollment in the Namwon Study and the Dong-gu study, ongoing community-based cohort studies in South Korea. A total of 1,103 controls (273 from HCES1 and 830 from HCES2) were genotyped by MEGA. Guangzhou Lung Cancer Study (GLCS): The GLCS is a case-control study including never-smoking women lung cancer cases and controls from Guangzhou, China.In this study, the DNA samples of 1,195 subjects from SWHS and GLCS were genotyped using whole exome sequencing (WES), and the DNA samples of 7,174 subjects from SWHS, HCES1, HCES2, FLCCA, and sFLCA were genotyped using the Multi-Ethnic Global Array (MEGA).

  Study phs002366

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144

• 300BCG study: human population variation of trained immunity

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

  Study EGAS50000000090

• Histone acetylome-wide association study on tuberculosis infection

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

  Study EGAS00001003118

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

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

  Study EGAS50000000735

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

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

  Study EGAS00001006202

• ATAC-seq data for two BCL11B-a subtype leukemia cases

  ATAC-seq was performed in two BCL11B-a subtype leukemia specimens to identify putative regulatory elements and allow comparison of motif enrichment in open chromatin to experimental and normal cell datasets. Raw paired-end reads were quality trimmed and adapter trimmed using TrimGalore (v0.4.4) with a quality score cutoff of Q20. The first 15 bp of each read were clipped to reduce the GC bias introduced by the Tn5 enzyme. Quality trimmed reads were mapped to the GRCh38 reference genome with BWA (v0.7.12-r1039) and converted to bam format using samtools64 (v1.2). Duplicate reads were marked using biobambam2 (v2.0.87). Bam files were submitted

  Dataset EGAD50000002472

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

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

  Dataset EGAD50000000340

• Bulk ATAC-Seq HiSeq2500 v4 reagents (100M reads)

  Human data for chromatin accessibility (ATAC-Seq) in eight B-cell precursors: HSC, CLP, pro-B, pre-B, Immature B, Transitional B, Naive B CD5-, Naive B CD5+ cells

  Dataset EGAD00001010909

• GATCI RNAseq fastqs

  Raw RNA sequence data (fastq) for the GATCI project

  Dataset EGAD00001005810

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• Genome-Wide Association Study of Lung Cancer Susceptibility in Never-Smoking Women in Asia

  To learn about the etiology of lung cancer among never-smoking women in Asia, we formed the Female Lung Cancer Consortium in Asia (FLCCA), which includes studies of lung cancer in Eastern Asia and conducted a GWAS. We analyzed a total of 5510 lung cancer cases and 4544 controls and identified 3 novel loci (Lan et al., 2012). Of these study subjects, 4922 lung cancer cases and 3959 controls are available for posting. Lan et al.., Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia. Nat Genet. 2012 Dec;44(12):1330-5. doi: 10.1038/ng.2456. Epub 2012 Nov 11. PubMed PMID: 23143601.

  Study phs000716

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

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

  Study phs003220

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

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

  Study phs003997

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

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

  Study EGAS00001007930

• Cell-type eQTLs for single-cell Mendelian Randomisation

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

  Study EGAS50000000687

• Centre Leon Berard - DAC - seq data Neuroendocrine tumors - B Gibert

  Review committee for the neuroendocrine tumor genetic data set uploaded by Benjamin GIBERT (CRCL), Anthony FERRARI (CLB) and Thomas WALTER (HCL)

  Dac EGAC50000000218

• Chromatin accessibility in OCI-AML22 cells

  ATAC-seq performed in OCI-AML22 subpopulations sorted based on CD34 and CD38 status

  Dataset EGAD50000001631

• SiMSen‑Seq

  High resolution amplicon-bases sequencing o screen for PIK3CA hot spot mutations

  Dataset EGAD50000001668

• input

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

  Dataset EGAD00001005209

• Dataset for gynecologic_cancer-RNA

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008856

• Dataset for melanoma-RNA

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008858

• Dataset for hematopoietic_malignancy-RNA

  Rare cancer sequencing data of 47 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008860

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• Mutational anysis of breast cancer stem cells

  Exome sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations��� (clones���) mutations will be detected. Based on cancer stem theory, each populations��� cells are derived from each cancer stem cells, which their numbers are not so different among different clones. Here, we separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. By comping two groups��� mutation, we identified mutations, which were only detected in stem cell population. These mutations could be the mutations in cells of small size populations, and maybe the important mutations to understand the heterogeneity of tumor tissues, progression, and/or prediction for the outcome to therapies.

  Study JGAS000304

• Single cell atlas of large B-cell lymphoma

  Large B-cell lymphomas (LBCL) are clinically and biologically heterogeneous lymphoid malignancies, shaped by complex tumor and microenvironments that play a critical role in disease progression. There has been no direct and comprehensive single-cell characterization of tumor microenvironment in LBCL that simultaneously captures lymphoid, myeloid, and stromal populations across a sufficiently large cohort to reveal reproducible and biologically meaningful patterns. Here, we performed single-nucleus multiome profiling, coupled with bulk DNA and RNA sequencing, on 232 tumor and control biopsies to comprehensively map cell subpopulations of LBCL. Through this integrative approach, we identified Lymphoma Microenvironment Archetype Profiles (LymphoMAPs)—distinct, reproducible patterns defined by the co-occurrence of functionally specialized cell subsets. We further characterized the cell-cell communication pathways that shape these transcriptional phenotypes within archetypes. Importantly, we discovered associations between specific LymphoMAPs and clinical and molecular features of LBCL, including response to CD19 CAR T-cell therapy. Our study provides a valuable resource of lymphoid, myeloid, and non-hematopoietic cell states in LBCL and offers a framework for understanding how the abundance and functional state of cells within the tumor microenvironment may drive inter-patient variability in therapeutic outcome.

  Study EGAS50000001022

• Whole exome and transcriptome analysis of UV-exposed epidermis and carcinoma in situ reveals early drivers of carcinogenesis

  Squamous cell carcinoma in situ (SCCIS) is a prevalent precancerous lesion that can progress to cutaneous squamous cell carcinoma (cSCC). Although SCCIS is common, its pathogenesis remains poorly understood. To better understand SCCIS development, we performed laser-captured microdissection of human SCCIS and adjacent epidermis to isolate genomic DNA and RNA for next generation sequencing. Whole exome sequencing (WES) identified UV-signature mutations in multiple genes including Notch 1-3 (GeneID:4851, GeneID:4853, GeneID:4854) in the epidermis and SCCIS and oncogenic TP53 (GeneID:7157) mutations in SCCIS. Novel gene families, including SCHLAFEN genes, contained UV/oxidative-signature disruptive (UVD) epidermal mutations that manifested positive selection in SCCIS. The frequency and distribution of NOTCH and TP53 mutations indicate that NOTCH mutations may precede TP53 mutations. RNA sequencing identified 1166 differentially expressed genes; the top 5 enriched GO biological processes included: 1) immune response, 2) epidermal development, 3) protein phosphorylation, 4) regulation of catalytic activity, and 5) cytoskeletal regulation. The NEURL1 ubiquitin ligase, which targets Notch ligands for degradation, was upregulated in SCCIS. Neuralized 1 protein was found to be elevated in SCCIS suggesting that increased levels could represent a novel mechanism for downregulating Notch during UV-induced carcinogenesis. The data from DNA and RNA sequencing of epidermis and SCCIS provide insights regarding SCCIS formation.

  Study phs002019

• DUX4 activates novel intergenic transcripts and isoforms in a tissue-specific context

  DUX4, a transcription factor driving zygotic genome activation during the embryonic cleavage stage in mammals, regulates the expression of genic and non-genic elements and modulates chromatin accessibility. Its misexpression in skeletal muscle causes Facioscapulohumeral muscular dystrophy (FSHD). The sporadic expression of DUX4 in FSHD muscle and the limitations of short-read RNA sequencing challenge, however, a comprehensive grasp of its consequences on the muscle transcriptome. Here, leveraging full-length isoform RNA sequencing with short-read RNA sequencing on DUX4-inducible myoblasts, we elucidated DUX4-induced transcriptomic changes within a myogenic context. DUX4 yields a complex transcriptome featuring numerous unannotated isoforms from known and novel loci. Moreover, we observed distinct isoform usage of DUX4 target genes between myogenic and embryonic cleavage states highlighting the distinct differences between DUX4 transcription factor activity in skeletal muscle and during the cleavage stage. We also identified ~1,400 unannotated intergenic isoforms predominantly originating from repetitive elements such as LTRs, LINEs, and SINEs. Integration with available datasets delineates the transcriptional and epigenetic landscape of these loci across myogenic and embryonic backgrounds. Like the cell type-specific isoform production, the usage of DUX4 binding sites at these intergenic loci is in part cell type-specific. Collectively, these findings demonstrate substantial and context-specific transcriptomic alterations induced by DUX4 further enriching our understanding of DUX4-induced muscle pathology.

  Study EGAS50000000503

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). 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 EGAS00001002643

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

  Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). 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 EGAS00001002642

• Glioblastoma epigenome profiling identifies SOX10 as a master regulator of molecular tumour subtype

  Glioblastoma in adult patients are classified into four subtypes, IDH, MES, RTK I, and RTK II, based on DNA methylation and RNA expression data. Tumour subtype transitions commonly occur during the treatment of glioblastoma patients, and transitions to the mesenchymal (MES) subtype have been associated with therapy resistance and adverse prognosis. Here, we generate DNA methylome and histone modification data of glioblastoma primary tumours and show that glioblastoma subtypes differ by their enhancer landscapes. Using Core Regulatory Circuitry analysis of H3K27ac data, and independent analysis of RNA-derived gene regulatory networks, we identified 38 subtype master regulators whose cell type-specific activities we mapped in single-cell RNA sequencing data. These analyses identified the chromatin modifier SRY-Box 10 (SOX10) as a master regulator in tumours of the RTK I subtype. In functional studies we demonstrate that SOX10 loss causes a transition of RTK I tumour cells to a mesenchymal cellular state by altering the accessibility of enhancer-rich chromatin regions and their occupancy by Bromodomain Containing 4 (BRD4), a dynamic constituent of super-enhancers. Treatment with the BRD4 inhibitor JQ1 blocked this transition. These data demonstrate the fundamental role of enhancer chromatin remodelling and master regulator activity in the establishment, maintenance and plasticity of glioblastoma cellular states. We also make our data publically browsable at https://dkfz-b060.github.io/gb_browse/

  Study EGAS00001003953

• RNA-sequencing of human skin samples obtained from SSc patients and healthy controls.

  Patient information SSc patients were recruited at the Department of Rheumatology of the Leiden University Medical Center (Leiden, The Netherlands). All patients met the American Rheumatism Association classification criteria for SSc (Subcommittee for scleroderma criteria 1980), and were classified according to LeRoy and Medsger criteria as either limited or diffuse cutaneous disease (LeRoy EC, Black C, Fleischmajer R, Jablonska S, Krieg T, Medsger TA Jr, Rowell N 1988). Institutional review board approval and written informed consent was obtained before patients entered this study. Two 4 mm skin biopsies were taken from a standardized location on the most proximal part of the lower arm, distal from the elbow. In 10 patients the skin biopsy came from a clinically affected area and in 4 patients the skin was locally unaffected. One sample was used for RNA sequencing and one sample was used for immunohistochemistry. Skin biopsies from healthy individuals were commercially sourced (Tissue Solutions, UK) and collected from donors undergoing skin resection surgery and after informed consent. To match the healthy skin with patients as much as possible, skin biopsies from healthy controls were also taken from a similar position (the under-arm (for 4 controls) and leg (for 2 controls)). Healthy skin donors were selected to match the age and sex of the SSc patient cohort. Biopsies from patients and controls were equally treated and were both stored at -80°C until RNA isolation was performed. RNA from frozen skin biopsies was isolated using RNeasy kit from fibrous tissue (Qiagen, the Netherlands). RNA quantity was determined by using SimplyNano 2000 and quality was assessed on Tapestation (Agilent, the Netherlands). All samples included in the study had a RIN score above 7.0. Transcriptome characterisation and analysis RNA sequencing was performed using polyA selection and a stranded protocol using Ion Torrent next generation sequencing technology (Service XS, The Netherlands). The Ion PI Template OT2 200 Kit v3 and Ion PI Sequencing 200 Kit v3 were used according to the manufacturer’s instructions. 20 samples were run on 11 PI chips. PI chip analyses, base calling and quality checks were performed using the Torrent Server Suite. An average of 42 million 100 bp reads was generated per sample. Following quality control, reads were aligned to the human genome (Homo sapiens GRh38.78) using Bowtie2 and STAR (Dobin et al. 2013; Langmead and Salzberg 2012). Reads were first aligned with STAR. For the unmapped reads from STAR, a second alignment step was performed using bowtie2 (local very sensitive options)

  Dataset EGAD00001003832

• Genome-Wide Discovery of Novel Breast Cancer Predisposing Mutations

  Cancer risk shows clear heritability, but the inherited genetic factors remain largely unknown. This project will seek to identify new genes in which mutations confer hereditary risk for early onset breast cancer, with important implications for both biological understanding and clinical prediction and prevention. Identifying cancer predisposing mutations can provide new biological insights and significantly impact important clinical decision making regarding treatment, surveillance and preventive approaches. Examples include the BRCA1 breast cancer susceptibility gene, which affects treatment decisions (surgical management), surveillance (frequent breast MRI) and prevention (oophorectory for prevention of ovarian cancer). Hereditary early onset breast cancer patients commonly present to Cancer Genetics clinics, but the majority of these patients do not have identifiable mutations in known candidate genes. Here, we will perform whole exome sequencing to discover novel cancer susceptibility genes. The patients have been recruited from Memorial Sloan Kettering Cancer Center (PIs Kenneth Offit and Zsofia Stadler) and Massachusetts General Hospital (PI Daniel Haber). All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000822

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Genomic analysis of Japanese gastric cancer (345 gastric cancers of NCC)

  As a contribution to the International Cancer Genome Consortium, whole exome sequencing of 345 Japanese gastric cancer (345 gastric cancers of NCC) with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer.

  Study EGAS00001002884

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Study EGAS00001003450

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• UTUC RNAseq data

  RNA sequencing of upper urinary tract urothelial carcinoma

  Dataset EGAD00001007667

• Plasma mutation profile of precursor lesions and colorectal cancer using the Oncomine Colon cfDNA Assay

  Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. Early detection of precursor lesions or early-stage cancer could hamper cancer development or improve survival rates. Liquid biopsy, which detects tumor biomarkers, such as mutations, in blood, is a promising avenue for cancer screening. To assess the presence of genetic variants in plasma cell-free tumor DNA from patients with precursor lesions and colorectal cancer using the commercial Oncomine Colon cfDNA Assay. Cell-free DNA (cfDNA) samples from the blood plasma of 52 Brazilian patients were analyzed. Eight patients did not have any significant lesions (five normal colonoscopies and three hyperplastic polyps), 24 exhibited precursor lesions (13 nonadvanced adenomas, ten advanced adenomas, and one sessile serrated lesion), and 20 patients with cancer (CRC). The mutation profile of 14 CRC-associated genes were determined by next-generation sequencing (NGS) using the Oncomine Colon cfDNA Assay in the Ion Torrent PGM/S5 sequencer.

  Study EGAS50000000471

• Acute Myeloid Leukemia samples - peripheral blood

  ATAC-seq performed in peripheral blood samples of patients affected by Acute Myeloid Leukemia (AML)

  Dataset EGAD50000001642

• Exome

  Exome Seq for EGAS00001001845

  Dataset EGAD00001002160