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• PYDP Papuan Y chromosome Diversity Panel

  The PYDP dataset includes 26 bam files of Y chromosome sequences for Papua New Guinean individuals from different locations, extracted from whole genome sequences. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer.

  Dataset EGAD00001008572

• Whole Genome Sequencing of Therapy-Related Myeloid Neoplasms

  The dataset consists of: 51 paired tumor/normal WGS samples (26 tumors and 25 normals), and 13 normal targeted samples.

  Dataset EGAD00001010026

• Identification of putative multiple myeloma (MM) susceptibility genes

  We sought to identify novel MM susceptibility genes using a collection of families with multiple cases of MM/MGUS, including 189 affected individuals from 40 families, and index cases from an additional 88 families, along with 170 early-onset (EO) MM cases (≤ 55 years). We analyzed a total of 347 affected individuals using whole exome (N=321) and whole genome (N=26) sequencing. Samples were identified and collected through nation-wide efforts in France, Sweden and Greece. We focused on rare (MAF<0.5%) germline protein truncating and likely deleterious missense variants in genes harboring variants in at least two families showing variant-disease segregation, and in additional index (≥2) and/or early-onset (≥2) cases.

  Study EGAS50000001259

• European Genome-phenome Archive 15th Anniversary Celebration

  2023 marks the 15th Anniversary of the EGA, jointly managed by the European Bioinformatics Institute (EMBL-EBI) and the Centre for Genomic Regulation (CRG). To mark the occasion, a simultaneous celebration was held in both institutions on the 13th of December 2023. The teams gathered online to play a quiz game and celebrate all the achievements and milestones with two wonderful anniversary cakes. In 2008, the European Genome-phenome Archive was created at the EBI-EMBL in Cambridge to guarantee that human genome and phenome data were available to the international scientific community while data privacy was preserved. The six-person staff at the beginning of the project is now far behind us, with a team that reaches the number of 35 members. Since 2013, the European Bioinformatics Institute and the Centre for Genomic Regulation share responsibility for The European Genome-phenome Archive (EGA). At that time, the EGA had data for about 0,5 petabytes. Currently, the Archive contains more than 12 petabytes. 2023 comes to an end with several good news. The EGA has been renewed as an ELIXIR Core Data Resource. This was announced during the GA4GH 11th Plenary held in San Francisco last September when ELIXIR-Beacon was also confirmed to be a GA4GH Driver Project. Thus, the Beacon API has maintained this title since 2018. What’s more, the first Federated EGA dataset is now live on our website. This year we also launched new services for EGA users in September. By the numbers, in 2023 the EGA counts 2.5 PB archived, 371 studies published, 208 new submitters and 19 active projects in which the team is participating, among others. We look forward to continuing to support your research in 2024!

  Blog 15-anniversary

• Combination_therapies_for_personalized_cancer_medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Study EGAS00001000655

• Single cell RNA sequencing data of advanced melanoma patients treated with checkpoint inhibitor immunotherapy

  Single cell RNA libraries were prepared using 10x Genomics Chromium Next GEM Single Cell 3’ v2 reagents. The samples were barcoded and each library were pooled with two samples at equimolar concentrations. The pooled libraries (n=4) were sequenced on the NextSeq 500 machine (Illumina) with paired-end sequencing and dual indexing as recommended in the manufacturer’s protocol; 26 and 98 cycles for the respective Read 1 and 2, and 8 cycles for i7 index.

  Dataset EGAD50000000493

• HERBY trial WES

  Whole exome sequencing of non-brainstem paediatric high grade glioma from the HERBY phase II randomised trial. DNA from 86 cases was subjected to Illumina paired end whole exome sequencing using a customised SureSelect Human All Exon V6 capture set. Germline DNA from whole blood was sequenced for 83 cases. 26 cases were sequenced from both fresh frozen tissue and FFPE material, 10 were sequenced from only fresh frozen material and 50 from only FFPE. Data is provided as bwa aligned BAM files

  Dataset EGAD00001004036

• Mitochondrial DNA sequencing of iPSC, parental cells, and iPSC derived cardiomyocytes

  The aim of this work was to analyze to which extent mitochondrial DNA (mtDNA) variants in human induced pluripotent stem cells (iPSC) originate from their parental cells or from de novo mutagenesis, and whether dynamics in variant heteroplasmy levels during prolonged expansion culture of iPSC are caused by inter- or intra-cellular selection or genetic drift. Hence, mtDNA of 26 early passage iPSC clones from, in total, 10 donors and the corresponding parental cell populations (here endothelial cells) were sequenced. Furthermore, 7 iPSC clones were expanded up to passage 50 and the change in variant heteroplasmy levels was monitored. Lastly, the effect of differentiation on the variant heteroplasmy levels was investigated during directed cardiomyocyte differentiation of 4 iPSC clones.

  Study EGAS00001005560

• A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

  The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect. The full dataset includes FASTQ files, target BED file, and MLPA results.

  Study EGAS00001002428

• 'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

  Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

  Study EGAS00001007347

• Genetics of Neuropsychiatric and Neurodevelopmental Disorders

  Although schizophrenia is a highly heritable disease, relatively little progress had been made in securely identifying the genetic causes of this disorder, and most instances of schizophrenia in the general population remain unexplained. One avenue of explanation for the genetic basis of schizophrenia, however, has been effectively closed by recent research. Genome-wide association studies (GWAS) have now shown that common variation makes at most a modest contribution to the risk of schizophrenia. At the same time that the role of common variation has been circumscribed by GWAS, however, the analysis of copy number variants that are detectable on a genome-wide scale has revealed and replicated a number of very rare variants that associate with schizophrenia. These rare copy number variants that have been implicated in schizophrenia, however, have one striking feature in common: they are all risk factors for other brain related disorders beyond schizophrenia such as mental retardation, autism and epilepsy. These findings argue that genetic risk factors may confer a highly penetrant vulnerability to neuropsychiatric disorder, which is then further modified by interacting genetic or environmental factors to determine the ultimate manifestation. Most schizophrenia collections that are being studied today, however, have been selected precisely for their homogeneity: including only schizophrenia patients with no comorbidities, or schizophrenia patients with relatives who have schizophrenia but no other neuropsychiatric conditions. These selection criteria are inconsistent with what we now know about the bulk of the genetic differences that have been associated with disease. The central hypothesis of this project is that there are rare genetic variants that strongly elevate the risk of various neuropsychiatric diseases, and that these risk factors can be identified most readily in families segregating multiple neuropsychiatric conditions.

  Study phs000682

• GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

  1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child&#39;s behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school&#39;s database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

  Study phs000852

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

  Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

  Dataset EGAD00001006415

• BLUEPRINT release August 2016, ChIP-Seq for band form neutrophil, on genome GRCh38

  ChIP-Seq data for 4 band form neutrophil sample(s). 26 run(s), 23 experiment(s), 23 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002454

• Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

  Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

  Dataset EGAD00001008021

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• PETAL Network: Outcomes Related to COVID-19 Treated With Hydroxychloroquine Among Inpatients With Symptomatic Disease (ORCHID) Trial

  ORCHID was a multicenter, blinded, placebo-controlled randomized trial conducted at 34 hospitals in the US between April 2 and June 19, 2020. Adults hospitalized with respiratory symptoms from severe acute respiratory syndrome coronavirus 2 infection were enrolled, with the last outcome assessment on July 17, 2020. The planned sample size was 510 patients with five interim analyses; however, the trial was stopped at the fourth interim analysis for futility with a sample size of 479 patients.The distribution of the day 14 clinical status score (measured using a 7-category ordinal scale) was not significantly different for patients randomized to receive hydroxychloroquine compared with placebo.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002299

• Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

  Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

  Study EGAS50000000470

• Hydroxyurea to Prevent Organ Damage in Children with Sickle Cell Anemia (BABY HUG) Phase III Clinical Trial and Follow-Up Observational Studies I and II

  Sickle cell anemia is associated with substantial morbidity from acute complications and organ dysfunction beginning in the first year of life. In 1995, the Multicenter Study of Hydroxyurea (MSH) (dbGaP phs002348) demonstrated that, in adults, hydroxyurea is effective in decreasing the frequency of painful crises, hospitalizations for crises, acute chest syndrome, and blood transfusions by 50%. The phase I/II study of hydroxyurea in children (HUG KIDS) demonstrated that children have a response to hydroxyurea similar to that seen in adults in terms of increasing fetal hemoglobin levels and total hemoglobin, and decreasing complications associated with sickle cell anemia. In addition, this study demonstrated that the drug does not adversely affect growth and development between the ages of 5 and 15. A pilot study of hydroxyurea (HUSOFT) given to children between the ages of 6 months and 24 months demonstrated that the drug was well tolerated and that the fetal hemoglobin levels rose and remained elevated compared to baseline with continued hydroxyurea administration. A Special Emphasis Panel (SEP) met on April 12, 1996 to review the results of the MSH trial and the progress to date of the HUG KIDS study. The SEP recommended that NHLBI undertake the BABY HUG trial. The BABY HUG Randomized Controlled Trial concluded that hydroxyurea treatment in very young children seemed to have an acceptable safety profile and to reduce complications of sickle cell anemia. However, more data were needed on the long-term safety of hydroxyurea use in very young children. As a result, follow-up studies were initiated. The Follow-Up Study II provided longer follow-up than Follow-Up Study I, and included more assessment types than Follow-Up Study I.The BABY HUG program consisted of three related studies, each of which has associated datasets and bio-specimens. A randomized controlled trial comparing hydroxyurea to placebo in very young children with sickle cell anemia (BABY HUG Randomized Controlled Trial) The first observational follow-up study of children from the randomized controlled trial (BABY HUG Follow-Up Study I). All children in Follow-Up Study I were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child. The second observational follow-up study of children from BABY HUG Follow-Up Study I. All children in Follow-Up Study II were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The purpose of the Randomized Controlled Trial was to determine if hydroxyurea can safely prevent early end organ damage in very young children with sickle cell anemia. The purpose of the BABY HUG Follow-up Study I was to provide structured follow-up of the children enrolled in the BABY HUG Randomized Controlled Trial, in order to characterize the long-term toxicities and unexpected risks (if any) associated with treatment with hydroxyurea at an early age. The objective of Follow-Up Study II was to obtain additional data about the long-term safety and efficacy of hydroxyurea use in children with Sickle Cell Anemia through at least the first decade of life.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002415

• 86 paired-end MiSeq 16S rRNA sequencing samples

  We compared bacterial communities in breast milk from teen (≤19 yr, n = 26) vs. adult (&gt;19 yr, n = 56) mothers, normal weight (BMI 18.5-24.9, n = 63) vs. overweight (BMI ≥ 25, n = 19) mothers, primiparous (parity = 1, n = 41) vs. multiparous (parity &gt; 1, n = 44), early (5-46d postpartum, n = 39) vs. established lactation (4-6 mo postpartum, n = 45), breastfeeding (EBF: PBF, n = 72) vs. mixed feeding (n = 11) and mothers with (Na/K ratio &lt; 0.6, n = 75) and without SCM (Na/K ration ≥ 0.6, n = 10).

  Dataset EGAD00001004160

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• Small cell number RNA-seq (400 cells per sample)

  Transcriptional profiles for stemB and proB cells harvested from either primary or secondary xenografts. This dataset contains six types of samples: - diagnostic stemB cells harvested from primary xenografts - diagnostic proB cells harvested from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with proB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with proB cells from primary xenografts

  Dataset EGAD50000001830