15077 results for "cancer studies using rna-seq"

in 21.87 milliseconds.

• Whole genome bisufite sequencing of smoking and non-smoking mother-child pairsBisufite sequencing, RNA-seq and ChIP-Seq data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

  Whole-blood samples of 16 mother-child pairs with differing maternal smoking behaviour were bisulfite treated and sequenced with deep coverage to identify smoking-associated differentially methylated regions.RNA-sequencing and ChIP-sequencing of 4 chromatin marks complete the data set and allow for integrative analyses, functional region annotation and to study the impact of epigenetic changes on gene expression.Longitudinal data spanning several years provides the means to investigate the stability of observed differences of all data types.

  Study EGAS00001000455

• BLUEPRINT: Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

  Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes (RNA-Seq) and epigenomes (ChIP-Seq H3K4me1,H3K4me3,H3K27ac) in four primary cell types: monocytes, in vitro differentiated naive, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, B-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

  Dataset EGAD00001001011

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559

• WXS and RNA-seq for 22 patients treated with radiation + immunotherapy

  Over 500 active clinical trials are investigating combination radiation (RT) and immune checkpoint blockade (ICB) as a cancer treatment; however, the majority of trials have found no positive interaction. We performed a comprehensive molecular analysis of a randomized phase I clinical trial of patients with non-small cell lung cancer (NSCLC) treated with concurrent or sequential ablative RT and ICB. Concurrent treatment was superior to sequential treatment in augmenting local and distant tumor responses and improving overall survival in a subset of patients with highly aneuploid tumors, but not in those with less aneuploid tumors. Our analysis suggested that concurrent treatment eliminated immunologically cold aneuploid tumors better than sequential treatment and improved patient outcomes. In addition, we report that RT alone decreased intratumoral cytotoxic effector T cell and adaptive immune gene expression signatures, in contrast to upregulation of key immune pathways after concurrent administration of RT and ICB. Our findings distinguish the differential genomic and transcriptomic effects of RT versus RT and ICB and challenge the prevailing paradigm that local ablative RT beneficially stimulates the immune response. We propose the use of tumor aneuploidy as a novel biomarker and therapeutic target in personalizing treatment approaches for patients with NSCLC treated with RT and ICB.

  Study EGAS00001006212

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• Single cell atlas of relapsed/refractory large B-cell lymphoma

  Relapsed/refractory large B-cell lymphomas (rrLBCL) are clinically and biologically diverse lymphoid malignancies with intricate microenvironments that play a key role in disease development. In this study, we used single-nucleus multiome profiling along with bulk DNA and RNA sequencing on 120 tumor and control biopsies to comprehensively characterize the various cell types and subsets found in rrLBCL tumors.

  Study EGAS50000001293

• Bulk RNASeq of metastatic colorectal cancer organoids treated with crenigacestat alone or in combination with cetuximab

  Bulk RNA sequencing was performed on mCRC organoids cultured under untreated conditions or treated with crenigacestat alone or in combination with cetuximab. This dataset was generated to investigate the transcriptional changes associated with combination therapy and to compare these profiles with the adaptive responses observed following cetuximab monotherapy in the corresponding ATOH1 wild-type and knockout organoid models.

  Study EGAS50000001422

• Genomic characterisation of SDH deficient renal cell carcinoma - RNA

  SDH deficient renal cell carcinomas are a rare and recently defined subtype of kidney cancer, often associated with an inherited mutation in one of the SDH gene subunits. This dataset sought to understand the genomic events that underpin tumour formation, from putative cell of origin, characterisation of the tumour microenvironment, to the genomic evolution of these rare tumours. We performed whole genome and RNA sequencing of 4 patients with SDH deficient renal cell carcinomas, including one patient who had an additional paraganglioma. An addition patient in this cohort had the initial diagnosis revised to a clear cell renal cell carcinoma.

  Dataset EGAD00001008470

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• sWGS data from 362 tumor with non muscle invasive bladder cancer and 30 blood samples (15 males and 15 females)

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 876 BAM files corresponding to the full WES dataset. This dataset contains 392 BAM files corresponding to the full sWGS dataset. Tumor samples were sequenced to median coverage of 2.14x (1.24-9.01).

  Dataset EGAD50000000732

• Discovering the Genetic Basis of Cleft Palate: CIDR

  Cleft palate (CP) is a common craniofacial structural birth defect caused by the incomplete closure of the palate (the structure separating the oral and nasal cavities), resulting in feeding, speech, and hearing problems. CP accounts for 33% of all orofacial clefts (OFCs) or approximately 1 in 1500 babies born worldwide. Although CP is commonly grouped with other types of orofacial clefts (e.g. cleft lip or cleft with cleft palate), CP is embryologically and epidemiologically distinct, suggesting a unique etiology. The risk of CP recurrence in first degree relatives is over 50-fold higher than the population risk, suggesting a strong genetic component. However, there have been a dearth of genetic studies for CP. Three well-powered genome-wide association studies and meta-analysis have revealed only two associated loci, neither of which account for a large portion of the genetic heritability in any population. The goal of this study is to elucidate the genetic architecture of CP by performing whole genome sequencing of case-parent trios in a well-phenotyped, multi-ethnic cohort. 

  Study phs002220

• Screening Protocol and Longitudinal Study of Bone Marrow Failure Syndromes and Cytopenias

  The purpose of this study is to characterize patients with Bone Marrow Failure Syndromes (BMFS) and to track the clinical course of patients with these diseases over time. An exact and comprehensive diagnosis at presentation is essential. Due to the sporadic nature of BMFS (aplastic anemia, myelodysplastic syndrome, paroxysmal nocturnal hemoglobinuria, pure red cell aplasia, amegakaryocytic thrombocytopenic purpura and large granular lymphocyte leukemia) most diseases have not undergone systematic long-term outcome studies. Individual diseases, combined under the collective entity of bone marrow failure syndromes, frequently overlap and evolve from each other. The frequency of complications, associations with other diseases, and genetic factors such as allelic polymorphisms are not well studied. Some of these syndromes are likely mediated by the cellular immune system. However, while target antigens are likely to be expressed on early hematopoietic cells, their identification has been unsuccessful. Hypothesis: Clinical and epidemiologic studies may, through etiologic clues and intricate laboratory testing, facilitate the understanding of the pathophysiology of BMFS and ultimately lead to implementation of better diagnostic tools and more targeted and rational therapies.

  Study phs000592

• Kids First: Genomics of Orofacial Clefts in the Philippines

  Orofacial clefts (OFCs) are the most common craniofacial structural birth defect in humans caused by incomplete formation of the upper lip and/or the palate. Over 4,000 children in the Philippines are born with an OFC every year, and the Filipino OFC birth prevalence rate of 1 in 500 live births is one of the highest in the world. Genome-wide association studies support a multifactorial etiology for OFCs, but common variants only account for up to ~25% of the heritable risk in any one population. Sequencing studies in diverse populations is essential to fully understand the genetic architecture of OFCs. The study goals of the Kids First project are to sequence a collection of case-parent trios from the Philippines, in order to identify de novo mutations and inherited rare variants, and understand the population differences in common variant signals in the Philippines versus other populations. Approximately 373 trios from the Philippines were selected for whole genome sequencing (WGS) as part of this Gabriella Miller Kids First project.

  Study phs002595

• Whole Exome Sequencing Study of TGFΒ Pathway Genes in HCV Liver Fibrosis

  Despite the astonishing progress in treating chronic hepatitis C virus (HCV) infection with direct-acting antiviral agents, liver fibrosis remains a major health concern in HCV infected patients, in particular due to the treatment cost and insufficient HCV screening in many countries. Only a fraction of patients with chronic HCV infection develop liver fibrosis. While there is evidence that host genetic factors are involved in the development of liver fibrosis, the common variants identified so far, in particular by genome-wide association studies, were found to have limited effects. Here, we conducted an exome association study in 88 highly selected HCV-infected patients with and without fibrosis. A strategy focusing on TGF-β pathway genes revealed an enrichment in rare variants of the endoglin gene (ENG) in fibrosis patients. Replication studies in additional cohorts (617 patients) identified one specific ENG variant, Thr5Met, with an overall odds ratio for fibrosis development in carriers of 3.04 (1.39-6.69). Our results suggest that endoglin, a key player in TGF-β signaling, is involved in HCV-related liver fibrogenesis.

  Study phs001902

• HipSci - Human Induced Pluripotent Stem Cells Initiative

  Human induced pluripotent stem (iPS) cells can be generated from adult tissues and differentiated into a range of specific cell types (Yamanaka and Blau, 2010). They therefore provide unprecedented opportunities for investigating disease mechanisms and understanding the phenotypic consequences of genetic variation within the normal population. HipSci brings together diverse constitutents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. Between 2013 and 2016 we aim to generate iPS cells from over 500 healthy individuals and 500 individuals with genetic disease. We will then use these cells to discover how genomic variation impacts on cellular phenotype and identify new disease mechanisms. Strong links with NHS investigators will ensure that studies on the disease-associated cell lines will be linked to extensive clinical information. Further key features of the project are an open access model of data sharing; engagement of the wider clinical genetics community in selecting patient samples; and provision of dedicated laboratory space for collaborative cell phenotyping and differentiation.

  Study EGAS00001001465

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Metabolic reprogramming has been described in rapidly growing tumors, which are thought to mostly contain fast-cycling cells (FCCs) that have impaired mitochondrial function and rely on aerobic glycolysis. Here, we characterize the metabolic landscape of glioblastoma (GBM) and explore metabolic specificities as targetable vulnerabilities. Our studies highlight the metabolic heterogeneity in GBM, in which FCCs harness aerobic glycolysis, and slow-cycling cells (SCCs) preferentially utilize mitochondrial oxidative phosphorylation for their functions. SCCs display enhanced invasion and chemoresistance, suggesting their important role in tumor recurrence. SCCs also demonstrate increased lipid contents that are specifically metabolized under glucose-deprived conditions. Increased fatty acid transport in SCCs is targetable by pharmacological inhibition or genomic deletion of FABP7, both of which sensitize SCCs to metabolic stress. Furthermore, FABP7 inhibition, whether alone or in combination with glycolysis inhibition, leads to overall increased survival. Our studies reveal the existence of GBM cell subpopulations with distinct metabolic requirements and suggest that FABP7 is central to lipid metabolism in SCCs and that targeting FABP7-related metabolic pathways is a viable therapeutic strategy.

  Study EGAS00001003251

• ETMR_Meth

  77 ETMR samples were profiled using methylation array. DNA from frozen tissue and formalin-fixed, paraffin-embedded (FFPE) materials were analyzed with the Illumina Infinium HumanMethylation450 (450k) and MethylationEPIC (EPIC) array according to manufacturer’s instructions and with a modified method that was previously described (Torchia et al. Cancer Cell. 2016; Triche et al. Nucleic Acids Res. 2013).

  Dataset EGAD00010001669

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to two different E.Coli strains and a dye control with three biological duplicates. Their original culture was harvested as a control. In total 10 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD00001005416

• Highly differentiated, fusion-negative rhabdomyosarcoma.

  Sequencing was performed using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 genes, previously linked to human cancer. Sequencing wa sperformed on an Illumina HiSeq 2500. 8 highly differentiated, fusion-negative rhabdomyosarcoma tumor samples were sequenced. BAM files are available for download.

  Dataset EGAD00001003887

• Sequencing data of primary uveal melanomas and their matched metastases

  We performed targeted DNA sequencing of primary uveal melanomas and their matched metastases from 35 patients, analyzing a total of 124 tissues. Sequencing was performed on an Illumina HiSeq 2500 instrument using a panel of 538 genes commonly involved in cancer. 124 BAM files were generated.

  Dataset EGAD00001004453

• TONIC study RNASeq

  Transcriptome sequencing of 97 matched TNBC breast cancer metastasis samples obtained from 50 unique patients assayed at two timepoints: at baseline (directly after patient randomization), and post-induction treatment or control waiting period. The included raw transcriptome sequencing data (fastq-format) were generated using Illumina HiSeq2500 instruments.

  Dataset EGAD00001004858

• Improved Detection and Identification of Microsatellite Instability Features in Colorectal Cancer

  In this study, we analyzed a series of colorectal cancers using a new sequencing technology that sequences more than 200 microsatellite regions in parallel. With this technology, we evaluated mono-, di- , tri- and tetranucleotide repeats to provide a broad spectrum of microsatellite instability (MSI) events. This deep sequencing technology provides greater than 2000X coverage and eliminates the need for PCR amplification. Because every read corresponds to a single DNA molecule, we eliminated artifacts introduced by PCR that obscured true MSI events. Also included in our analysis is a new method for detection of somatic copy number changes in 83 cancer genes, with which we can infer chromosomal instability (CIN) status.

  Study phs001914

• OxyTarget mtDNA seq

  We studied 44 rectal cancer patients enrolled onto a prospective population-based biomarker study, who were planned for curative-intent radiation therapy before definitive surgery, yet at high risk of metastatic progression beyond the pelvic cavity. The patients had full-length mtDNA sequencing of whole blood (WB) and peripheral blood mononuclear cells (PBMC), sampled at the time of diagnosis. Metastatic events were recorded up to 60 months of follow-up after completion of the multimodal treatment.

  Dataset EGAD00001007992

• Single cell RNA sequencing of mononuclear cells from synovial fluid of patients with rheumatoid arthritis

  Mononuclear cells were collected from synovial fluid of anti-citrullinated positive antibodies (ACPA)-positive rheumatoid arthritis patients (n=8) and ACPA-negative RA patients (n=8). Global cell types (i.e., no enrichment) were obtained from these cryopreserved synovial fluid mononuclear cells (SFMC) samples and immediately fixed and processed using the GEM-X Flex Gene Expression Reagent Kits (10x Genomics) according to protocol. Following Gel Bead-in Emulsion (GEM) generation, samples were processed using the standard manufacturer’s protocol. Once sequencing libraries passed standard quality control metrics, libraries were sequenced on an Illumina NextSeq2000 P4 100 cycle reagent kit with the following read structure: R1: 28, R2: 90, I1: 10, I2: 10. Libraries were sequenced to obtain a read depth greater than 10,000 reads/cell for gene-expression (GEX). FASTQ files are made available. More detailed information can be obtained in Argyriou A. et al, Annals of the Rheumatic Disease, 2025.

  Dataset EGAD50000001801

• The evolutionary history of human colitis-associated colorectal cancer

  Inflammatory bowel disease confers an increased lifetime risk of developing colorectal cancer (CRC), and colitis-associated CRC (CA-CRC) is molecularly distinct from sporadic CRC (S-CRC). Here we have dissected the evolutionary history of CA-CRC using multi-region sequencing. Exome sequencing was performed on fresh-frozen multiple regions of carcinoma, adjacent non-cancerous mucosa and blood from 12 CA-CRC patients (n=55 exomes), and key variants were validated with orthogonal methods. Genome-wide copy number profiling was performed using SNP arrays and low-pass whole genome sequencing on archival non-dysplastic mucosa (n=9), low-grade dysplasia (LGD, n=30), high-grade dysplasia (HGD, n=13), mixed LGD/HGD (n=7) and CA-CRC (n=19). Phylogenetic trees were reconstructed, and evolutionary analysis used to reveal the temporal sequence of events leading to CA-CRC. 10/12 tumors were microsatellite stable with a median mutation burden of 3.0 single nucleotide alterations (SNAs) per Mb, around 20% higher than S-CRC (2.5 SNAs/Mb), and consistent with elevated aging-associated mutational processes. Non-dysplastic mucosa had considerable mutation burden (median 47 SNAs), including mutations shared with the neighboring CA-CRC, indicating a pre-cancer mutational field. CA-CRCs were often near-triploid (42%) or near-tetraploid (21%) and phylogenetic analysis revealed that copy number alterations (CNAs) began to accrue in non-dysplastic bowel, but the LGD/HGD transition often involved a punctuated catastrophic CNA increase.

  Study EGAS00001003028

• EuCANCan: EUropean-CANadian Cancer network

  The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

  Blog eucancan

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Buccal

  Targeted NanoSeq in buccal epithelium obtained longitudinally from a number of donors. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 55 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015618

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Blood

  Utilising Targeted NanoSeq, we hope to explore the driver landscape in unprecedented detail in donors from TwinsUK. These donors have paired buccal swabs and data from this will help contextualise that work. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015619

• Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

  Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015620

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Blood

  Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015623

• Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Buccal

  Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

  Dataset EGAD00001015622

• Exome sequencing of UK Birth Cohorts - Millennium Cohort Study

  Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights from population genetics to rare disease associations. Avon Longitudinal Study of Parents and Children (ALSPAC)recruited 14,775 babies of predominantly White ethnicity in the Avon county of south-west England between 1991 and 1992. Born in Bradford (BiB) is similarly focused on a particular local area, the city of Bradford in the north of England, and recruited 13,858 babies between 2007 and 2011, of whom ~41% self-report as white British and ~59% as other ethnicities, predominantly Pakistani. Millennium Cohort Study (MCS) is a national cohort that recruited 18,827 children born between 2000 and 2002, intentionally over-sampling areas with high child poverty, large ethnic minority populations, and smaller UK nations (Wales, Scotland and Northern Ireland) Available here is a subset of exome-sequenced parents and children from these studies (CRAMS and post-QC VCFs) as detailed in https://doi.org/10.12688/wellcomeopenres.22697 [doi.org]. Phenotypic data is also available by submitting an application to the corresponding cohort: https://cls.ucl.ac.uk/cls-studies/millennium-cohort-study/ [cls.ucl.ac.uk]

  Dataset EGAD00001015372