12310 results for "cancer rna-seq"

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• RNAseq of fibroblasts

  RNA sequencing data of fibroblasts from 3 controls and 3 patients with RBMX variants.

  Dataset EGAD50000002371

• README-for-EGAS00001004349-linking-HIPO-K09R-RNA-files

  Dataset EGAD00001006785

• RNA sequencing of pituitary neuroendocrine tumors (PitNETs)

  This study reports a multiomic analysis of pituitary neuroendocrine tumors.

  Study EGAS50000001414

• RNA sequencing BRAF fusion partners

  Contains RNAseq data for 14 transduced/non-transduced organoids

  Dataset EGAD00001005380

• Direct RNA sequencing of 10 postmortem human brain samples

  Contains fast5 data for each of the 10 samples sequenced.

  Dataset EGAD00001015347

• The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation

  In this study, we will apply a multi-staged approach to reveal genes harboring rare variants that are associated with aggressive PCa. Whole-exome sequencing (Aim 1a) of 2,774 aggressive cases and 2,776 non-aggressive cases of European ancestry will be conducted followed by rare variant analysis of single sites and gene burden testing to identify novel susceptibility loci/genes for aggressive disease. We will validate the most significantly associated genes (~500) through targeted sequencing in an additional 6,415 aggressive and 5,586 non-aggressive cases and 1,890 controls (Aim 1b). Next, we will investigate the clinical predictive utility of the genes/variants identified in 2,291 cases in the STHM3 trial who are undergoing biopsy based on PSA and genetic risk score stratification (Aim 2). Through this tiered approach we expect to significantly advance knowledge of aggressive PCa etiology and health disparities as well as guide the development of early detection and prognostic strategies for the subset of men who are most susceptible to this fatal form of disease. In this case-case study of aggressive vs non aggressive prostate cancer, aggressive cases are defined as prostate cancer as cause of death, (T4 disease or T3 disease) and Gleason 8+. Non-aggressive cases are men with T1/2 disease and Gleason ACKNOWLEDGMENTS and CONTRIBUTING SITES CAPS, PROCAP, STHM1, STHM2: Swedish Cancer Society (CAN 2016/818), Swedish Research Council (2014/2269).STHM3: Stockholm County Council (Stockholms Läns Landsting).MEC: Funding provided by the National Cancer Institute: Understanding Ethnic Differences in Cancer, 2U01CA164973 and The Genetic Basis of Aggressive Prostate Cancer, The Role of Rare Variation, 5R01CA196931-02.ATBC: The ATBC Study is supported by the Intramural Research Program of the U.S. National Cancer Institute, National Institutes of Health, and by U.S. Public Health Service contract HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services.COSM: The Swedish Research Council/National Research Infrastructure Grant (VR 2014/6397; VR 2015/5997) The Swedish Cancer Foundation (CAN 2013/456; CAN 2016/727)CPSII: The authors express sincere appreciation to all Cancer Prevention Study II participants and to each member of the study and biospecimen management group. The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study-II cohort.MCCS/APCS/PCFS: The Melbourne Collaborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria and further supported by Australian National Health and Medical Research Council (NHMRC) grants 209057 and 396414. The Aggressive Prostate Cancer Case-Control Study (APCS) was funded by NHMRC grant 623204. The Prostate Cancer Family Study (PCFS) was fully funded by Cancer Council Victoria. Cancer Council Victoria funds the continuing maintenance and updating of the MCCS, APCS and PCFS. Cases and their vital status are ascertained and followed up through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database.PLCO: The Prostate Lung Colorectal Ovarian Cancer Screening Trial (PLCO) was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, US National Institutes of Health, Department of Health and Human Services. EPIC: The coordination of EPIC is financially supported by International Agency for Research on Cancer (IARC) and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London which has additional infrastructure support provided by the NIHR Imperial Biomedical Research Centre (BRC). The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l'Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), German Institute of Human Nutrition Potsdam- Rehbruecke (DIfE), Federal Ministry of Education and Research (BMBF) (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS) - Instituto de Salud Carlos III (ISCIII), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology - ICO (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A19170 and C8221/A29017 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford). (United Kingdom). DFCI: Linda and Arthur Gelb and Rebecca and Nathan Milikowsky. HPFS and PHS: The Health Professionals Follow-up Study was supported by U01 167552 and P01 CA228696 from the National Cancer Institute, and with support from the Prostate Cancer Foundation. The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490 and HL34595.Northwestern: P50CA180995 (Catalona) 08/01/15 – 07/31/20 NIH/NCI SPORE in Prostate Cancer; The Urological Research FoundationPROMPT: MRC UK - Project reference G0500966, Cambridge BRC infrastructure funding, Cambridge Biomedical Research Campus (BRC-1215-20014), CRUK Cambridge Cancer Centre infrastructure funding (they are requesting this statement is written in blue for publications).ICR: This work was supported by the NIH R01 grant 5R01CA196931-02. The samples from the UK were from UKGPCS and PrompT. The UKGPCS study was supported by Cancer Research UK (grant numbers C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. We also acknowledge The Institute of Cancer Research, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK for their ongoing support. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust.Funding:CIDR grant X01HG008336

  Study phs001524

• Clonal Lineage Tracing of Primary Human Cortical Progenitors, Cell Type Profiles in the Brain Vasculature and Genotyping Data for 22q11DS and Control iPS Lines

  We sought to characterize the cell types produced by individual human cortical progenitors and describe their lineage relationships. We labeled individual human cortical cells with a massively complex lentivirus library encoding a GFP reporter gene and a molecular barcode that could be captured by standard 3' scRNA-seq methodologies. We then cultured the labeled human cells for 6 weeks in either a 1) mouse cortical astrocyte co-culture system or 2) in the mouse cortex as a xenograft. In a separate experiment, we maintained human cortical tissue slices in organotypic slice culture for 12 days. GFP+ cells were then isolated by FACS and then captured on the 10x chromium scRNA-seq platform. An additional sample was labeled by lentivirus and briefly cultured for 3 days prior to being mixed with mouse 3T3 cells in order to perform a cell mixing experiment ("barnyard") to benchmark our methodologies. We found that human individual cortical progenitors gave rise to both excitatory and inhibitory neurons as well as glia.We also sought to characterize the adult brain vasculature in both vascular malformations and non-malformed tissue. We use the 10x chromium scRNA-seq platform across 10 individuals (5 control and 5 arteriovenous malformations). We find broad disregulation across multiple cell types including the immune cells and find a specific monocyte subtype to contribute to a rupture phenotype. We also find a novel population of fibromyocytes in both conditions.Finally, we confirmed the genotype status of iPS lines that were derived from either karyotypically normal control individuals or from DiGeorge Syndrome patients carrying the 22q11.2 deletion using the Illumina Infinium Global Screening Array v3.0.

  Study phs002624

• NOWAC blood-based breast cancer case-control study

  Tumor-host interactions extend beyond the local microenvironment and cancer development largely depends on the ability of malignant cells to hijack and exploit the normal physiological processes of the host. Although abnormalities in a host’s systemic immunity are associated with increased cancer susceptibility, the functional interplay between tumor cells and circulating immune cells in regulating tumorigenic responses is unclear. We employed the Norwegian Women and Cancer study, a large prospective population-based cohort study, to identify gene expression changes in blood cells that provide a robust and reproducible diagnostic signal specific to breast cancer patients. We further show that circulating blood cells in breast cancer patients are enriched in genes involved in systemic immunosuppression and the motility, metabolism, growth, and proliferation of immune cells. By mining of the cancer-associated blood transcriptome, we identified immune mediators or biomarkers that could permit early detection of breast cancer and open avenues to novel targeted immunotherapies.

  Study EGAS00000000134

• Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing (WGS) data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional and mutation type specific frequencies in tissue and cell-free DNA (cfDNA) of cancer patients that were associated with replication timing and other chromatin features. A machine learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of lung cancer patients, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches, and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

  Study EGAS00001007248

• CLL_targeted_exome_sequencing

  Aim to characterise cancer gene landscape in CLL, particularly in cases with mutated POT1 gene. Treatment-naïve CLL cases will be interrogated by targeted exome sequencing using a cancer gene panel.

  Study EGAS00001001963

• Reference_DNA_standards_for_GCLP_pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Study EGAS00001001173

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• Evolution of Structural Rearrangements in Prostate Cancer Intracranial Metastases

  Intracranial metastases in prostate cancer are uncommon but clinically aggressive. We sought to characterize prostate cancer intracranial metastases in order to improve our understanding of their pathogenesis and to promote the search for new treatment strategies. We evaluated the clinical and molecular characteristics of 36 patients with metastatic prostate cancer to either the dura or brain parenchyma. We performed whole genome sequencing (WGS) on samples from 21 patients. The WGS samples include 10 intracranial prostate cancer metastases, as well as WGS of primary prostate tumors from men who later developed metastatic disease (n=6) and non-brain prostate cancer metastases (n=26).

  Study phs003357

• Targeted_analysis_of_chondrosarcoma_cancer_genes

  Targeted analysis of chondrosarcoma cancer genes

  Study EGAS00001001765

• Identification of Cancer Predisposition Genes in Breast Cancer Families

  Breast cancer has a significant genetic component. The strongest epidemiologic risk factor is family history of the disease. Familial studies have identified a number of genes contributing to increased risk. Of these, the highly penetrant BRCA1 and BRCA2 genes account for the majority of families in whom disease-causal mutations have been identified. However, mutations in other genes have been associated with predisposition to breast or breast and ovarian cancer including (CHEK2, ATM, PALB2, RAD51C, RAD51D). Together these genes account for less than 20% of excess familial breast cancer risk and do not explain ~50% of high-risk families referred for genetic testing. This significant gap in our understanding of the genetic basis of breast cancer poses a significant barrier to our ability to identify women at increased risk, who would benefit greatly from appropriate clinical management. To identify additional breast cancer predisposition genes whole exome sequencing of familial high-risk breast cancer patients was undertaken. DNA samples from 50 pairs of breast cancer patients from high-risk breast cancer families with no pathogenic mutations in the BRCA1 or BRCA2 breast cancer predisposition genes were subjected to whole exome sequencing. The goal was to select candidate predisposition genes for further validation studies based on sharing of putative protein inactivating mutations among both members of each family and/or the frequency of inactivating mutations among the 50 families.

  Study phs000480

• MPNST study - scRNA

  10X single nucleus RNA data of one MPNST patient, including one primary and five recurrence regions

  Dataset EGAD50000002565

• Multi-omics RNA profiling of glioblastoma patient tissues

  Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Dataset EGAD00010001895

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• Targeted MCC-seq

  The capture panel targets the functional methylome in human whole blood. Regions incorporated in the panel design included hypomethylated windows generated from merged WGBS data.

  Dataset EGAD50000000286

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• SCNA-Seq of tumor DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping of corresponding tumor material

  Dataset EGAD00001002150

• ChIP sequencing from a collection of PFA tumors

  ChIP data from PFA (n = 10). Raw data provided as FASTQ. Data generated on Illumina NovaSeq 6000 PE50.

  Dataset EGAD00001009045

• Paired-end Whole Exome-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 50 paired-end Whole Exome sequencing samples from 3 patients. 3 normal blood samples are also included.

  Dataset EGAD00001010289

• NiCOL Study Target-seq dataset

  10 samples sequenced in Target-sequencing of a panel of 571 genes (Illumina NovaSeq 6000) - Raw FASTQ data - Annotated VCF

  Dataset EGAD00001010911

• H3K27ac ChIPseq of cohesin-mutated and wildtype adult AMLs

  ChIP-seq targeting the H3K27ac histone modification in cohesin-mutated (STAG2 or RAD21 mutation) and cohesin wildtype (CTRL-AMLs) AMLs.

  Dataset EGAD00001011204

• Genomic Characterization of African-American Prostate Cancer

  African-American men have the highest incidence and mortality rate from prostate cancer. This study represents a whole exome sequencing study of prostate cancer samples from African-American men. We performed exome sequencing and analysis of prostate tumors and matched normal tissues to identify somatic mutations and insertion/deletions across this cohort. All sequencing was performed at the Broad Institute. This study has the potential to identify novel recurrently mutated genes in prostate cancer and improve our understanding of prostate cancer in African-Americans.

  Study phs000945

• Human pan-cancer plasma cfRNA study - raw data

  This study contains mRNA capture sequencing data from plasma of 266 different human donors. The first, pan-cancer, cohort covers 25 high-grade to metastatic cancer types (8 cancer patients per type) and a control group (8 healthy donors). The validation cohort comprises additional plasma samples from ovarian, prostate and uterine cancer patients (12 per type) as well as additional samples from controls (22 new and 8 repeated). Samples were sequenced on a NovaSeq 6000 and are provided in FASTQ format.

  Study EGAS00001006755

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Study EGAS00001002891

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Study EGAS00001002892

• WGS of gastric cancer in the Japanese population (81 gastric cancers of NCC)

  As a contribution to The International Cancer Genome Consortium Accelerating Research in Genomic Oncology (ICGC ARGO), whole-genome sequencing of 81 cases from Japanese gastric cancer with various histological subtypes has been conducted. This study aims to reveal the landscape of structural variants (SV) in gastric cancer and analyze mutational and rearrangement signatures simultaneously

  Study EGAS00001006051

• Epigenomic profile of diverse cancer

  Epigenomic profile of diverse cancer.

  Study EGAS00001004352

• Mapping the Evolution of T Cell States During Response and Resistance to Adoptive Cellular Therapy

  We investigated single T cell transcriptional states that define donor lymphocyte infusion (DLI) response and resistance from cryopreserved bone marrow mononuclear cells from 15 patients with relapsed chronic myeloid leukemia (CML) after allogeneic hematopoietic stem cell transplant. By integrating bulk ATAC-seq data from sorted T cell populations from these bone marrow samples, we also defined gene regulatory networks that underlay these clusters.

  Study phs002877

• DAC for a single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Dac EGAC50000000226

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• DOGMA-seq data and analysis

  Data and analysis of DOGMA-seq assay of Lin- sorted live cells from bone marrow tissue of 12 patients with MDS or AML (before treatment with 5-azacytidine). Data files are paired-end reads in FASTQ format from the Illumina NovaSeq 6000 sequencer. Analysis files are outputs from Cellranger ARC: .h5 peaks and genes matrix file, atac_fragments.tsv.gz file and its index. Samples with ADT assay have analysis files from kallisto, bustools, and kite: ADT_features.txt, ADT_barcodes.txt, ADT_matrix.mtx.

  Dataset EGAD50000001377

• SUM-seq data for Primary T-cells differentiated to helper subtypes

  Briefly, naive CD4+ T cells were isolated from PBMCs obtained from buffy coats from three healthy human donors, and differentiated into Th0, iTreg, Th2, Th1, Th17, and IFN-β-activated subsets. This allowed us to study the differentiation of naive CD4+ T cells into distinct helper subsets under the influence of a specific cytokine environment. Following 5 days of differentiation, T cells were left unstimulated or re-stimulated with phorbol 12-myristate 13-acetate (PMA) and ionomycin to assess their functional responses. Thus, this SUM-seq experiment consisted of 36 multiplexed conditions (3 donors x 6 stimulations x with/without re-stimulation). Single-cell chromatin accessibility and gene expression data is provided as demultiplexed fastq files.

  Dataset EGAD50000001204

• Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

  We performed scRNA-seq of patient-derived glioblastoma cells alone or after co-culture with human iPSC-derived cerebral organoid cells. Transcriptional changes implicated in the invasion process that are coherent across patient samples indicate that GBM cells reactively upregulate genes required for their dispersion. Potential interactions between GBM and organoid cells identified by an in silico receptor-ligand pairing screen suggest functional therapeutic targets.

  Study EGAS00001003852

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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 EGAS00001000947

• Processed naive T cell AIRR-seq data

  This dataset contains processed productively and non-productively rearranged TCR sequences (tsv file format) from bulk AIRR-seq of naive peripheral blood CD4+ T cells from 103 subjects with celiac disease and 103 control donors. Raw sequences have been processed with presto and Change-O as detailed in the linked publication in order to filter by quality, create consensus sequences and collapse identical rearrangements, and analysed with IgBlast. The dataset also contains an accompanying metadata file (csv).

  Dataset EGAD50000002731

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• 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

• Genome-Wide Association Study of Breast Cancer in the African Diaspora - the ROOT study

  The paucity of data on the genetic epidemiology of breast cancer for racial/ethnic groups other than those of European ancestry hinders the development of innovative interventions to reduce health disparities. Women in the African Diaspora experience a disproportionate burden of pre-menopausal breast cancer in comparison to all other races for reasons that remain unknown and understudied. This higher proportion of early-onset breast cancer might suggest a stronger genetic component in these populations. Genome-wide association studies (GWAS) have revealed several genetic loci that confer risk of breast cancer. Because all GWAS started the discovery stage in women of European ancestry and replicated mainly in women of European ancestry, we propose a novel approach for a GWAS in indigenous African women to identify alleles associated with breast cancer risk which will then be replicated in other populations. This innovative design builds on our current understanding of the etiologic heterogeneity in breast cancer and the distribution of breast cancer molecular subtypes which differ between women of African ancestry and women of European ancestry. The major objective of the proposed studies is to get to the "root" causes of breast cancer by identifying breast cancer risk alleles in a pooled sample of women of African ancestry and to replicate our findings in other populations. To achieve this objective, we conducted a case control study of breast cancer in women of African ancestry, including Africans living in Nigeria, African Americans and African Barbadians. We will genotype ~3800 individuals using the Illumina HumanOmni2.5-Quad platform. We will conduct both standard and novel genetic analyses of the data to map genes associated with breast cancer susceptibility, verify genotyping and carry out fine-mapping studies in genes or regions showing association with breast cancer risk, and replicate in other African American and non-African American populations. By pooling unique resources from studies throughout the African Diaspora, this study has the potential to identify risk alleles in several genes that contribute to increased breast cancer risk and may have implications for early detection, prognosis and treatment of breast cancer in ALL women. This should ultimately lead to improved outcomes for those who suffer a disproportionate burden of early-onset breast cancer.

  Study phs000383

• Evaluation of the ERa binding region activity in breast and endometrial cancer

  Evaluate the activity of ERa binding site activity in breast and endometrial cancer.

  Study EGAS50000000009

• Genome-Wide Association Study of Sporadic and Familial Testicular Germ Cell Tumors

  Case-Control Study:Testicular germ cell cancer has been increasing among men during most of the 20th century. Despite this increase, the etiology of testicular cancer is poorly understood. To better understand the molecular epidemiology of testicular cancer, the National Cancer Institute and the Department of Defense are conducting a case-control study of testicular cancer among military servicemen. The project includes obtaining biosamples and questionnaire data from all participants. Pre-diagnostic serum samples are available from the approximately 1,000 cases and 1,000 controls enrolled in the study. Multiple-Case Family Study:In a parallel project, we are also studying families in which 2 or more testicular cancers have occurred. Among those men diagnosed with testicular cancer, about 1-3 percent report a family history of the disease (FTGCT). Brothers of affected individuals are 8 to 10 times more likely to develop testicular cancer, and men whose fathers had testicular cancer are four times more likely to develop testicular cancer, when compared with the relatives of men who have never had testicular cancer. Large-scale genetic linkage studies have failed to identify one or more rare, highly-penetrant testicular susceptibility genes. Rather, it appears that these familial clusters are due to the combined effects of multiple more common genes with low penetrance (so-called "polygenic inheritance"). Our cohort of FTGCT families was assembled to characterize this syndrome's clinical phenotype, and to discover the full range of cancer susceptibility loci that influence TGCT pathogenesis.

  Study phs001303

• Different malignant tumor samples including lung cancer, colon cancer and breast cancer.

  Genomic DNA was purified from tumor cells and normal cells in cancer patients; We sequenced those genomic DNAs using 10X Genomics sequencing technologies, and analyzed genomic structural variations.

  Study JGAS000360

• Early and Late Onset Colorectal Cancer Genomic Data

  A clinically and genomically annotated Early onset colorectal cancer and late onset colorectal cancer. This study aimed to identify genomic characteristics of early-onset colorectal cancer (EOCRC) compared to late-onset cases. Whole-genome sequencing (WGS) was performed on EOCRC and late-onset colorectal cancer (LOCRC) tissues and blood samples to analyze their genomic profiles.

  Dataset EGAD50000000774

• OCCAMS_Oesophageal_Cancer_Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Study EGAS00001001382

• RNA_sequencing

  All cancers arise due to somatically acquired mutations in their genomes which alter the function of key cancer genes. Understanding the critical mutational events underlying the development of cancer is paramount for advancing prevention, early detection and effective treatment of the disease. Breast cancer is the most common cause of cancer death among women. Extraordinary recent advances in sequencing now make it a realistic aim to sequence large numbers of breast cancer genomes to find somatic mutations on a massive scale. NB bam files for manuscript A_Proteomic_Chronology_of_Gene_Expression_through_the_Cell_Cycle_in_Human_Myeloid_Leukemia_Cells are now available at the following link:http://www.ebi.ac.uk/ena/data/view/ERP008483

  Study EGAS00001000310