13384 results for ""pdc"+"heritage+language"+census+study"

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• Human NXPE1 mediates variation in sialic acid O-acetylation in Colon Tissue

  Sialylation, and its modifications, have important consequences for development, differentiation and immune system regulation in nearly all human tissues. An accounting of all the genes responsible for modifying sialic acids is incomplete, with only one pathway for O-acetylation being well-defined in humans. Using whole genome sequencing of normal human colorectal tissue we identify a haplotype on chromosome 11 that is associated with differences in mild periodic acid Schiff staining (mPAS), a marker of acetylation of sialic acids. Of the genes in this region, only SNPs from NXPE1 correlate perfectly in a validation data set. NXPE1 protein expression by IHC also correlates with mPAS staining patterns in homozygous, as well as heterozygous colon crypts that have undergone spontaneous gain of the mPAS phenotype. Manipulation of NXPE1 expression with CRISPR-Cas9 causes changes to modified sialic acid levels in both 2D cell line and 3D normal colon organoid models. These findings suggest NXPE1 may cause O-acetylation of sialic acids in colorectal tissue, potentially defining NXPE as a new family of sialic acid-modifying genes.

  Study EGAS00001007704

• Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma

  The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT’s regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as druggability for future translational studies and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

  Study EGAS00001008140

• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Dataset EGAD00001000817

• Assessment of genetic and epigenetic variation in human IPS cells-RNA

  In order to progress human induced pluripotent stem cells (hiPSCs) towards the clinic, several outstanding questions must be addressed. It is possible to reprogram different somatic cell types into hiPSCs and from studies in the mouse, it appears that an epigenetic memory of the starting cell type is carried over to hiPSCs. However a comprehensive comparative study of the characteristics of these hiPSCs has been missing from the literature. Importantly studies which aimed to address these aspects of hiPSCs have used cells from different patients. In order to avoid this important confounding variable and to keep the genetic background constant, tissue samples were procured from the patients and reprogrammed to iPS cells. The transcriptomes of these iPS cells will be compared. Protocol: primary cultures of cells were reprogrammed to iPS cells. RNA was extracted using a standard column extraction kit.

  Dataset EGAD00001000604

• GDAP - Genome Diversity in Africa Project (2021-02-12)

  The Genomic Diversity in Africa Project (GDAP) started with the plan to develop a genomic resource from African populations, characterise genomic diversity and population history, and facilitate clinical studies in Africa. Currently, 25 individuals from 24 ethnolinguistic groups have been whole-genome sequenced at high depth totalling 585 individuals. An additional 41 individuals have been sequenced with 10X Genomics libraries. At this stage, the initial curation of this dataset has been finished and we are performing the analysis in coordination with our collaborators. The current state of the GDAP represents a very diverse panel of African populations that maximizes geographical and ethnic variation and represents a great starting point to achieve the aforementioned goals. However, southern sub-Saharan countries, Bantu speakers and hunter gatherer groups are currently underrepresented, despite being crucial to understand the evolutionary history of the continent. After extensive effort to collate studies documentation, we finally have the opportunity to sequence 600 new individuals from these groups, including countries as Gabon, Rwanda and Zambia, and address these deficiencies. We aim to proceed with the same strategy: to sequence at high depth 25 individuals with standard PCR free libraries, with 2 additional individuals with 10X Genomics Chromium libraries per ethnolinguistic group. The former allows a good representation of variants down to low frequency in any given population, and the latter allows accurate phasing and the analysis of structural variation. By including these new populations, we want to investigate three crucial questions in African history in addition to the initial objectives: the Bantu expansion, the evolutionary history of hunter gatherers and the transatlantic slave trade. Additionally, the expanded dataset will help us better discover the genetic variation present in Africa and characterize the African pangenome. 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/ . This dataset contains all the data available for this study on 2021-02-12.

  Dataset EGAD00001006965

• Genome Diversity in Africa Project: Uganda (2021-02-17)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics . This dataset contains all the data available for this study on 2021-02-17.

  Dataset EGAD00001006976

• Fetal origins of malignant germ cell tumours

  Germ cell tumours (GCTs) are a collection of benign and malignant neoplasms derived from primordial germ cells (PGCs). They are uniquely able to generate embryonic and extraembryonic tissues, which in malignant GCTs carries prognostic and therapeutic significance. The developmental pathways underpinning GCT initiation and histogenesis are incompletely understood. Here, we studied the phylogenetic and transcriptional diversity of 15 malignant gonadal GCTs and four normal testis biopsies by sequencing 131 whole genomes and 416 transcriptomes from 14 gonadal histologies, excised by laser capture microdissection. Our findings demonstrate that tumours were initiated by whole genome duplication likely in embryogenesis, within ~5-8 cell divisions post-PGC specification, followed by chromosome 12p gains associated with invasive disease. Of note, 12p imbalances were not only generated through GCT-typical isochromosomes, but also through non-isochromosomic configurations. Whilst tumours developed along homogenous phylogenetic pathways, they spawned manifold tissues independent of genetic subclonal diversification. A key feature of GCT tissues was the expression of fetal-specific genes. The transcriptional diversity notwithstanding, we found universal transcriptional elements correlated with hallmark 12p gains. Overall, our study reveals stereotyped phylogenies and transcriptomes underpinning the development of GCT that originate in fetal life and may lend themselves to therapeutic manipulation.

  Dataset EGAD00001007037

• Phylogenetic reconstruction of adult blood cancer reveals early origins and lifelong evolution - WGS

  Mutations in cancer-associated genes drive tumour outgrowth. However, the timing of driver mutations and dynamics of clonal expansion that lead to human cancers are largely unknown. We used 580,133 somatic mutations from whole-genome sequencing of 1013 clonal haematopoietic colonies to reconstruct the phylogeny of haematopoiesis, from embryogenesis to clinical disease, in 12 patients with myeloproliferative neoplasms which are blood cancers more common in older age. JAK2V617F, the pathognomonic mutation driving the majority of these cancers, was acquired in utero or childhood, with upper estimates of age of acquisition from 33 weeks gestation to 10.8 years, in all 5 patients in whom JAK2V617F was either the only or the first driver event.  Driver mutations associated with age-related clonal haematopoiesis occurred prior to or following JAK2V617F,  as independent clonal expansions in JAK2V617F-mutated patients, and as large clonal expansions in JAK2V617F-unmutated patients . These mutations were also acquired in utero or childhood, with DNMT3A mutations occurring by 8 weeks of gestation to 7.6 years across 4 patients, and PPM1D mutation occurring by age 5.8yrs in a patient with MPN lacking phenotypic driver mutations. Sequential driver mutation acquisition was common, separated by decades across life, and often outcompeted ancestral clones. The mean latency between JAK2V617F acquisition and clinical presentation was 30 years (range 11-54 years). Rates of clonal expansion were inferred from phylogenetic trees and varied substantially (3% to 190% expansion/year), were affected by additional driver mutations, and were predictive of latency to clinical presentation. Driver mutations and rates of expansion would have been detectable in blood one to four decades before clinical presentation. This study reveals how driver mutation acquisition early in life with life-long growth and evolution underlie adult myeloproliferative neoplasms, providing opportunities for early detection and intervention and a new paradigm for cancer development.

  Dataset EGAD00001007714

• Dataset RNAseq from regions of insitu and invasive human mammary ductal disease

  BAM files from RNAseq study from regions of insitu and invasive human mammary ductal disease

  Dataset EGAD00001008586

• Genomic Advances in Sepsis (GAinS): RNA-seq

  Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 34 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected on the first, third and/or fifth day following ICU admission. RNA was extracted from leukocytes isolated at the bedside using LeukoLOCK kits. We have previously identified sepsis response signatures (SRSs), transcriptomic endotypes that are associated with differential early mortality (Davenport et al, Lancet Respir Med, 2016; Burnham et al, AJRCCM, 2017) and response to treatment in a clinical trial (Antcliffe et al, AJRCCM, 2018). We generated RNA sequencing data on 903 samples, including 134 samples repeated from our previously released microarray data. Libraries were prepared using NEB Ultra II Library Prep kits (Illumina) and sequenced on a NovaSeq 6000. Reads were aligned to the reference genome (GRCh38) using STAR and gene counts quantified using featureCounts (annotation Ensembl v99). Counts were TMM-normalised and log-transformed. Following QC, processed data were available on 864 samples from 667 unique patients.

  Dataset EGAD00001008730

• Molecular risk stratification in patients with T1 colorectal cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have 'born-to-be-bad' aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world's largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3' RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Dataset EGAD00001010890

• Somatic mutation and selection at epidemiological scale - TwinsUK_RENanoSeq_Buccal

  Utilising restriction enzyme NanoSeq, we hope to explore the somatic mutation burden and mutational signatures in buccal cells from TwinsUK donors. Some donors have paired blood samples and data from this will help contextualise that work. All donors have paired Targeted NanoSeq data from buccal swabs. 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 EGAD00001015621

• Somatic mutation and selection at epidemiological scale - Sanger_NanoSeq_RandD

  Bottleneck sequencing of human tissue including neurons, cord blood, sperm 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/. 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 EGAD00001015624

• Intratumoral Heterogeneity and Clonal Evolution Induced by HPV Integration.

  The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines revealed a unique form of structural variation, termed heterocateny here, characterized by heterogeneous, interrelated, and repetative patterns of concatemerized virus and host DNA segments. Evidence of heterocateny was detected in extrachromosomal and/or intrachromosomal DNA in all cases. Unique breakpoint sequences shared across structurally heterogeneous virus-host concatemers within each cancer facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that unstable virus and virus-host concatemers in ecDNA or integrated form mediate insertion into and excision from chromosomes, capture, rearrangement, and rolling-circle amplification of host DNA, and chromosomal rearrangements. The data indicate that heterocatena is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intra-tumoral heterogeneity and clonal evolution.

  Study EGAS00001006652

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• Submitter Portal

  Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submissions. To start a new submission, click on “Create a Submission”.In this phase, you have the option to add any collaborator(s) as well as their permissions (“Read only”, “Read & Write” or “Full Access”). Please note that to add a collaborator, they must also have a submitter role. When adding a collaborator, please enter the user’s full email address in the search field and select the user. For security reasons, the portal does not display partial matches, so the full email address must be entered.The collaborator option is available while the submission is open. In the event that the submission is closed, you will need to reopen it. To do this, you only need to make a small modification in any objects within the submission, for example, copy and paste a title or description of the submission. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on Add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batches by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv, and the sample will be created.Add a single sample: complete the mandatory fields with the metadata information of your sample.  Further information can be found in the Submission Tour5. Create Experiment Register an experiment with ​information about the sequencing methods, protocols, and machines. Experiments generate the connection between the samples and the study. Further information can be found in the Submission Tour6. Create Run Samples, experiments, and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batches by using a template. Batch upload: download the template and complete it with the sample file linkage. Upload the run.csv, and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh.Add single run: select the file format, sample, and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded to your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF, and phenotype linkage to samples. The analysis is an EGA-specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). If you would like your dataset to be added to the cBioPortal instance, please review the cBioPortal documentation.Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested, please delete them from your SFTP INBOX after finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more files to a closed submission, you will need to reopen the submission where the dataset is registered.Please note that you can only modify datasets that begin with the ID EGAD5XXXXXXX.  Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission ID (EGA0XXX). Reopen the submission where the dataset is located: to reopen a submission, simply register new metadata, such as runs or analyses, and the submission will automatically reopen and appear on the main page. You can also do a small edition, such as copying and pasting a title or description. Take The Tour The Submitter Portal Take The Tour is a visual guide of all the steps described previously about how to start a submission. Tutorial In this tutorial, we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

• Genomic Diagnosis and Individualized Therapy of Highly Penetrant Genetic Diabetes

  The most common and well-known causes of diabetes are type 1 and type 2 diabetes; however, there are many other etiologies of diabetes. At least 1-2% of diabetes cases result from high penetrance single gene defects, most commonly in a gene encoding either a transcription factor involved in beta cell development and function or the enzyme glucokinase (GCK). Others have mutations in transcription factors necessary for beta cell development and function. This subset of monogenic diabetes cases is autosomal dominant and is known as "Maturity-Onset Diabetes of the Young" (MODY). Patients with type 1 diabetes are insulin dependent, meaning they lack insulin production and therefore require multiple daily injections of insulin, as well as multiple times a day blood glucose monitoring. This can be quite burdensome. Type 2 diabetes is predominantly an insulin resistance problem and can often be managed with pills initially, but there are many who also require insulin either at diagnosis or later on in their disease course. Usually, monogenic diabetes is misdiagnosed as type 1 or type 2 diabetes and thus treated suboptimally. Those with monogenic diabetes, due to a defect in a gene encoding a transcription factor, respond extremely well to a class of oral diabetes medications called sulfonylureas. Those with GCK-MODY often have a mild, stable, fasting, nonprogressive hyperglycemia for which pharmacological treatment is often not necessary. It is important to accurately diagnose our patients with the correct etiology to their diabetes for a multitude of reasons. Accurately diagnosing a patient with MODY, for example, can predict their clinical course and we can tailor treatment accordingly. If diagnosed with a transcription factor MODY, we can try switching the patient from insulin to an oral sulfonylurea, and if diagnosed with a GCK-MODY, we can consider discontinuing pharmacological treatment altogether. With specific tailoring of treatment, we would hope to improve quality of life by discontinuing perhaps multiple daily injections of insulin and glucose checking as these may not be necessary. In addition, we would hope to improve glycemic control with an eventual decreased cost to society by decreasing the complication rate of diabetes, resulting in less specialty referrals, lab tests, supplies and procedures. Further, given MODY is an autosomal dominant condition with a 50% chance of inheritance to first-degree family members, we could offer testing to asymptomatic family members which could lead to prevention and/or early diagnosis and treatment. Overall, testing for monogenic diabetes is underutilized clinically. Testing is being done in the U.K., but in the U.S. we are lagging behind. This is most predominantly due to lack of knowledge and concern over cost. In addition, it is difficult to differentiate the relatively small number of monogenic diabetes cases from the larger number with type 1 and type 2 diabetes as each of these etiologies have overlapping characteristics. In fact, many patients with monogenic diabetes are being misdiagnosed with type 1 and type 2 diabetes. There are recommendations set forth by different societies on who to consider screening for monogenic diabetes. However, these recommendations are difficult to employ clinically as they are general recommendations, there is no specific algorithm, and they are based on varying levels of evidence. The purpose of this study is to implement a personalized diabetes medicine program to enhance the identification of individuals and families affected by highly penetrant diabetes gene mutations through a combination of systematic screening and genetic testing at the University of Maryland Center for Diabetes and Endocrinology, the Baltimore VA Medical Center and additional partner centers at Geisinger Health System and Bay West Endocrinology Associates, and other UM outpatient clinics. Our hope is to develop an approach that can be eventually implemented across the United States so that we can more often uncover the correct etiology to diabetes, tailor treatment accordingly, and test asymptomatic family members.

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• Detroit Research on Cancer Survivors (ROCS) and Disparities and Cancer Epidemiology - Colorectal Cancer (DANCE)

  The goals for this study were as follows:1. Enroll a total of 5,060 African Americans newly diagnosed with cancer into the Detroit Research on Cancer Survivors (Detroit ROCS) Cohort. These population-based cases will be ascertained through the Detroit Metropolitan Detroit Cancer Surveillance System (MDCSS), a founding member of the NCI SEER Program. Participation at baseline will include a written, web-based, or telephone interview, saliva and/or blood collection, and tumor block retrieval, with detailed cancer-related information coming from the MDCSS registry and medical records.2. Enroll a subgroup of colorectal cancer patients identified through the Louisiana Tumor Registry (LTR). An additional 500 colorectal cancer patients, approximately half non-Hispanic white and half African American, will be identified through the LTR and enrolled into the ROCS protocol. The survey is the same survey administered to the ROCS cohort. The Louisiana (“DANCE-CRC”) cohort will not be followed beyond baseline, and blood will not be collected (tumor tissue, however, will be collected, deidentified, and sent for processing through Dr. Rozek's laboratory at Georgetown University).The proposed cohorts will provide for a broad research agenda evaluating cancer outcomes in African Americans across a variety of factors from individual, provider, health care system and community perspectives. These factors include tumor characteristics driving individualized treatment planning, quality of life after a diagnosis and recurrence. Utilizing the MDCSS registry, we will enroll a large population-based sample of African-American cases with lung, breast, colorectal, and prostate cancers and their caregivers resulting in a cohort that will provide substantial benefit to the cancer research community. KCI has a strong history of research in the African-American community and the faculty represents a breadth of experience that includes clinical oncology, genetic epidemiology, environmental exposures, quality of life, treatment decision making, racism/discrimination, and health behaviors. Drs. Schwartz and Beebe-Dimmer have been and will continue to be generous collaborators with other institutions to ensure that this resource will be extensively utilized. The proposed overall cohort will be the only one of its kind, to our knowledge, filling a substantial gap in our understanding of the determinants driving cancer outcomes in African Americans. In addition to registry data detailing cancer specifics, yearly surveys have collected information about individualized treatment experiences, heath histories, family histories, quality of life after a diagnosis, recurrence and caregiving. Population: Adult cancer survivors (see inclusion criteria in next section) Molecular Technologies: Genotyping: Infinium Expanded Multi-Ethnic Genotyping Array (MEGAEX) DNA Sequencing: Illumina NovaSeq X Plus using XLEAP-SBS (sequencing by synthesis) Whole genome sequencingPrincipal Findings: The preliminary data collected reinforces differences by race in factors affecting cancer outcomes. Variants in DNA damage repair genes and HOXB13 may be important cancer risk factors for Black men diagnosed with prostate cancer, and are more frequently observed in men with a family history of cancer. ROCS participants reported high rates of a family history of cancer. The high rate of eligibility for Cancer genetic counseling among ROCS participants supports the need for interventions to increase referrals and uptake of genetic counseling among African Americans 60% of ROCS participants reported participating in regular physical activity (PA), with 24% reporting ≥150 min/wk. There were no differences by sex, but prostate cancer survivors were the most likely to report participating in regular PA, whereas lung cancer survivors were the least likely. Survivors who reported participating in regular PA reported higher health-related quality of life and lower depression. More African American than White survivors reported financial hardship and limiting care. More White than African American survivors reported utilizing assets, while more African American survivors reported cancer-related debt. Data available in dbGaP: Individual phenotype data Individual genotype data Individual sequencing dataSample types: Germline DNA

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• Mechanisms of Therapy Driven Clonal Evolution in Oncogenic RAS Mutant Relapsed Acute Lymphoblastic Leukemia

  Although multi-agent combination chemotherapy is curative in a significant fraction of childhood acute lymphoblastic leukemia (ALL) patients, 20% of cases relapse and most die due to chemo-refractory disease. Here we used whole-exome and whole-genome sequencing to analyze the mutational landscape and pattern of clonal evolution at relapse in pediatric ALL cases. These analyses showed that ALL relapses originate from a common ancestral precursor clone of the diagnosis and relapsed populations and frequently harbor mutations implicated in chemotherapy resistance. RAS-MAPK pathway activating mutations in NRAS, KRAS and PTPN11 were present in 24/55 (44%) cases in our series. Notably, while some cases showed emergence of RAS mutant clones at relapse, in others, RAS mutant clones present at diagnosis were replaced by RAS wild type populations. Mechanistically, functional dissection of mouse and human wild type Kras and mutant Kras (Kras G12D) isogenic leukemia cells demonstrated induction of methotrexate resistance, but also improved response to vincristine, in mutant Kras- expressing lymphoblasts. These results identify chemotherapy driven selection as a central mechanism of leukemia clonal evolution and pave the road for the development of tailored personalized therapies for the treatment of relapsed ALL.

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• Transcriptome of Chronic Pain and Disease

  The Functional Genomics Section (FGS) is a part of the National Institute of Dental and Craniofacial Research (NIDCR) within the National Institutes of Health (NIH). Research at the FGS focuses on understanding the mechanics involved in nociception through both clinical samples from patients with chronic pain and mouse models of pain. Pain is relayed from the periphery to the central nervous system through specialized sensory neurons known as nociceptors. The cell body of nociceptors resides in neuronal structures that branch off of the spinal cord known as dorsal root ganglia (DRG). The DRG is a heterogenous tissue containing not only sensory neurons like nociceptors, but also glial cells, capillaries, fibroblasts, and resident macrophages. The interaction between the nociceptors and these DRG cell types can have a significant role in affecting neuronal hyperexcitability and downstream pain sensitivity. To better understand the cellular factors involved in producing conditions of chronic pain, DRGs from consenting organ donors were collected from individuals experiencing pain disorders such as painful diabetic neuropathy and rheumatoid arthritis. A multi-omics approach is being used to identify molecular mechanisms that lead to pain hypersensitivity in patients with chronic pain.  

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• Detection of Genes Predisposing to Hematologic Malignancies

  We have been conducting genetic studies on families at high risk of different hematologic malignancies, in order to define the related tumors in the families, define precursor and other related conditions, and map and identify susceptibility genes. We have focused mainly on four types of lymphoid malignancies: chronic lymphocytic leukemia (CLL), Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), and Waldenström macroglobulinemia (WM). A few families with a rare lymphoma subtype, hairy cell leukemia (HCL) are included. In addition, single large pedigrees with acute myeloid leukemia (AML), and juvenile myelomocytic leukemia (JMML) are included. Families are ascertained for having at least two patients with the same hematologic malignancy and are classified by the type of malignancy that predominates in the family. Multiple types of lymphoid malignancies are often found in the same family. Other data has shown that these conditions aggregate together in families. Verification of cancer diagnoses is obtained through medical records, pathology reports, and flow cytometry. Family members with precursor traits are also included, monoclonal B-cell lymphocytosis (MBL) in CLL families and IgM monoclonal gammopathy of undetermined significance (MGUS) in WM families.

  Study phs001219

• Epigenomes and Transcriptomes of Brain Samples of Schizophrenics and Controls

  We examined the effects of antipsychotic medications on the cell-specific epigenomics and transcriptomics in the frontal cortex of schizophrenic subjects. We performed ChIP-seq (H3K4me3 and H3K27ac) and RNA-seq on neuronal and non-neuronal nuclei of postmortem frontal cortex samples from two cohorts of schizophrenics, either previously treated or not with antipsychotic medications, and control subjects individually matched by sex and age. In total, we tested 29 schizophrenics (15 untreated and 14 treated patients) and their matched control samples. Two replicates were produced on each brain sample for each assay. ChIP-seq data were generated using MOWChIP-seq (Zhu et al., PMID: 31666743) and RNA-seq data were produced using the combination of SMART-seq2 (Picelli et al., PMID: 24385147) and a Nextera XT DNA library preparation kit. The filename contains the information on the experimental group, the number of the sample within the group, the type of the brain nuclei, the epigenomic/transcriptomic data set (either H3K27ac or mRNA), and the number of replicate. For example, “SCZ-1-untreated-neuron-H3K4me3-R1” refers untreated schizophrenic sample #1, replicate 1 ChIP-seq data on H3K4me3.

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• Clonal Evolution and Transcriptomic Analysis of Chronic Lymphocytic Leukemia Treated with Ibrutinib

  Disease progression has been increasingly appreciated with the use of ibrutinib to treat chronic lymphocytic leukemia (CLL). Understanding the pattern of clonal evolution and transcriptomic changes during the early treatment period with ibrutinib may provide insight into the mechanisms of resistance. We performed whole exome sequencing on sequential samples with matched germline controls from 61 patients with CLL during the first 12 months of ibrutinib monotherapy or ibrutinib in combination with rituximab. Additionally, RNA sequencing was done on a subset of 14 patients treated with ibrutinib monotherapy. The presence of clonal shifts was associated with an increased risk of disease progression, suggesting that resistant clones are more likely to emerge in CLL with greater evolutionary capacity.This cohort was later augmented with additional data (including data from 15 additional patients). In total, this second set of data contained whole exome sequencing (31 samples), RNA sequencing (6 samples) and reduced representation bisulfite sequencing (67 samples) for CLL samples and used them to identify expression subtypes of CLL. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

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• E5103 Correlative Studies

  ECOG-ACRIN E5103 (E5103) was a phase III adjuvant breast cancer trial that randomized 4994 patients with node-positive or high-risk node-negative breast cancer to intravenous doxorubicin and cyclophosphamide every 2 or 3 weeks (at the discretion of treating physician), for four cycles of adriamycin and cyclophosphamide (AC) followed by 12 weeks of weekly paclitaxel (80 mg/m2) alone (Arm A), or to the same chemotherapy with either concurrent bevacizumab (Arm B), or concurrent plus sequential bevacizumab (Arm C). To develop predictive genetic biomarkers for chemotherapy efficacy and toxicities, we have successfully performed genome-wide genotyping and whole exome sequencing in the germline (blood) DNA of 3215 and 672 patients, respectively, from the E5103 trial to investigate the association of genetic variants with chemotherapy efficacy and toxicities. Case and control studies were performed with genome-wide analyses (GWAS) and whole exome analyses (WES) across all arms of E5103 to identify genotypes at single-nucleotide polymorphisms (SNPs) and deleterious gene mutations that were associated with paclitaxel-induced peripheral neuropathy (TIPN). Through GWAS, we have identified a SNP, rs3125923, and through WES, Cytochrome P450 oxidoreductase (POR), that was significantly associated with grade 3-4 TIPN.

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• The Genomic Landscape of Endocrine Resistant Advanced Breast Cancers: Paired Pre- and Post-endocrine Therapy Samples.

  The genomic evolution of breast cancers exposed to systemic therapy and its effects on clinical outcome have not been broadly characterized. We integrated the genomic sequencing of 1918 breast cancers, including 1501 hormone receptor-positive tumors, with detailed clinical information and treatment outcomes. Functional mutations in ERBB2 and loss-of-function mutations in NF1 were more than twice as common in post-endocrine therapy tumors compared to treatment-naive tumors. Additional alterations in the MAPK pathway (EGFR, KRAS among others) and in estrogen receptor transcriptional regulators (MYC, CTCF, FOXA1 and TBX3) were also more common compared to hormonal therapy-naive tumors. To determine whether candidate genomic lesions in the MAPK pathway and estrogen receptor transcriptional regulators were present prior to therapy or whether such lesions arose under the selective pressure of therapy, we performed whole-exome sequencing in select patients who had adequate samples acquired prior to and after progression on endocrine therapy. In total, 95 specimens corresponding to 30 treatment-naive primary tumors, 35 post-treatment tumors, and 30 normal samples were sequenced from 30 patients with endocrine-resistant metastatic breast cancer.

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