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• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• The chemotherapeutic CX-5461 is extremely mutagenic and may increase cancer risk

  The chemotherapeutic agent CX-5461 or pidnarulex has been fast-tracked by the US FDA for treatment of BRCA1-, BRCA2-, and PALB2-mutated cancers. It is under investigation in Phase I/II clinical trials. Here we find that although CX-5461 exhibits synthetic lethality in BRCA1-/BRCA2-deficient cells, it also causes extensive, non-selective, collateral mutagenesis in all cells, to magnitudes that exceed known environmental carcinogens, raising public health concerns regarding its potential for promoting secondary cancers.

  Study EGAS50000000023

• sn-RNAseq profiling of the impact of a cytokine storm model in human cardiac organoids

  We developed conditions to model conditions of diastolic dysfunction caused by inflammatory factors in human cardiac organoids. Our organoid model is based on conditions promoting maturation (Mills et al., PNAS, 2017 and Voges et al., In Revision) and incorporating human pluripotent stem cell derived cardiomyocytes, epicardial cells, fibroblasts, endothelial cells and pericytes. Following 15 days of differentiation (Voges et al., Development, 2017) we formed human cardiac organoids incorporating both our multicellular differentiation (Mills et al., PNAS, 2017) and additional endothelial cells (Voges et al., In Revision). After another 12 days of maturation in 5 days maturation medium and 5 days weaning medium (Voges et al., In Revision) human cardiac organoids were either treated with weaning medium or “cardiac cytokine storm” comprised of 100 ng/ml IFNg, 10 ng/ml IL-1 β and 10 µg/ml poly(I:C). After 48 hours human cardiac organoids were harvested and snap frozen in -80C before nuclei isolation and single nuclei RNA sequencing.Pooled hCO (~40) were homogenized in 4 mL lysis buffer (300 mM sucrose, 10 mM Tris-HCl (pH = 8), 5 mM CaCl2, 5 mM magnesium acetate, 2 mM EDTA, 0.5 mM EGTA, 1 mM DTT)(all Sigma-Aldrich) with 30 strokes of a dounce tissue grinder (Wheaton). Large pieces of hCO were allowed to settle and homogenate was passed through pre-wetted 40 µm cell strainers (Becton Dickinson). Remaining hCO material in the douncer was resuspended in 4 mL and the douncing and filtering steps were repeated twice. All steps of the homogenization were performed on ice. The filtered homogenate was centrifuged at 1500 x g for 5 min at 4oC. Nuclei pellets were then re-suspended in PBS. A fraction of resuspended nuclei were then stained with hoechst nuclear stain (1:500 dilution) and counted on a haemocytometer under fluorescent microscope.The nuclei were then re-centrifuged (1500 x g for 5 min at 4°C) and resuspended at a density to load ~5,000 nuclei per sample. Cell were loaded into the Chromium Controller (10X Genomics) for gel bead emulsion (GEM) formation. Library preparation was conducted according to the manufacturer’s recommended protocol using the Chromium Next GEM Single Cell 3’ GEM, Library & Gel Bead Kit v3.1. Libraries were sequenced on the NextSeq 500/550 v2 (Illumina) with 150 bp reads.In the snRNA-seq we note the lower than expected percentage of non-myocytes and the loss of endothelial cells (Mills et al., PNAS, 2017 and Voges et al., In Revision), indicating the protocol requires further optimization for hCO samples.

  Study EGAS00001005174

• Atypical 3q26/MECOM rearrangements genocopy inv(3)/t(3;3) in acute myeloid leukemia

  Acute myeloid leukemia (AML) with inv(3)/t(3;3)(q21q26) is a distinct WHO recognized entity, characterized by its aggressive course and poor prognosis. In this subtype of AML, the translocation of a GATA2 enhancer (3q21) to MECOM (3q26) results in overexpression of the MECOM isoform EVI1 and monoallelic expression of GATA2 from the unaffected allele. The full-length MECOM transcript, MDS1-EVI1, is not expressed as the result of the 3q26 rearrangement. Besides the classical inv(3)/t(3;3), a number of other 3q26/MECOM rearrangements with poor treatment response have been reported in AML. Here we demonstrate, in a group of 33 AML patients with atypical 3q26 rearrangements, MECOM involvement with EVI1 overexpression, but no or low MDS1-EVI1 levels. Moreover, the 3q26 translocations in these AML patients often involve super-enhancers of genes active in myeloid development (e.g. CD164, PROM1, CDK6 or MYC). In more than 50% of these cases allele specific GATA2 expression was observed, either by copy number loss or by an unexplained allelic imbalance. Altogether, atypical 3q26 recapitulate the main leukemic mechanism of inv(3)/t(3;3) AML, namely EVI1 overexpression driven by enhancer hijacking, absent MDS1-EVI1 expression and potential GATA2 involvement. Therefore, we conclude that both atypical 3q26/MECOM and inv(3)/t(3;3) can be classified as a single entity of 3q26-rearranged AMLs. Routine analyses determining MECOM rearrangements, EVI1 and MDS1-EVI1 expression are required to recognize 3q-rearranged AML cases.

  Study EGAS00001004325

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Epithelioid haemangioendothelioma (EHE) case series from the Stafford Fox Rare Cancer Program

  Nine EHE cases with comprehensive histologic and molecular profiling from the Walter and Eliza Hall Institute of Medical Research Stafford Fox Rare Cancer Program were collated via nation-wide referral to the Australian Rare Cancer Portal. Molecular analysis of RNA, DNA or both was possible in seven of nine cases. Survival was highly variable and unrelated to molecular profile. DNA sequences for two cases are deposited here.

  Study EGAS00001007474

• Genetic variants of the COL4A3, COL4A4, and COL4A5 genes contribute to thinned glomerular basement membrane lesions in sporadic IgA nephropathy patients

  Contribution of pathogenic COL4A3/COL4A4/COL4A5 variants to sporadic IgAN is still unclear. Whole exome sequencing was performed in sporadic IgAN patients with thinned glomerular basement membrane lesions and variations in COL4A3/COL4A4/COL4A5 genes were screened and evaluated. 37 different diagnostic variants in COL4A3/COL4A4/COL4A5 gene in 38 patients (31.1%) were identified.

  Study EGAS00001006519

• Identification of genetic etiology of CAMRQ2

  We aimed to identify genetic etiology of cerebellar ataxia, mental retardation, and disequilibrium syndrome (CAMRQ). Targeted sequencing of the entire CAMRQ2 locus, 7.1 Mb interval on chromosome 17p13, in three affected individuals and two obligate carriers uncovered the mutation associated with CAMRQ2.

  Study EGAS00000000099

• NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing

  This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.

  Study phs001607

• NHLBI TOPMed - NHGRI CCDG: Penn Medicine BioBank Early Onset Atrial Fibrillation Study

  Cases with early-onset atrial fibrillation were selected from the Penn Biobank based on an age of atrial fibrillation onset prior to 61 years of age, and in the absence of a myocardial infarction, heart failure or severe valvular disease.

  Study phs001601

• The molecular landscape of colorectal cancer reveals genetic mutations - COCA-CN

  We collected tumor samples and adjacent nomal mucosae from 46 patients with colorectal cancer in surgical operation from 2014 to 2016 in the First Affiliated Hospital of Chongqing Medical University (Chongqing, China) and the Research Institute of Surgery, Third Military Medical University (Chongqing, China). the qualified captured library of each sample was then loaded on Illumina HiSeq 2000 (Illumina, San Diego, CA) platforms and subjected to high-throughput sequencing.

  Dataset EGAD00001003304

• The molecular landscape of colorectal cancer reveals genetic mutations（17 cases）

  We collected tumor samples and adjacent nomal mucosae from 17 patients with colorectal cancer in surgical operation from 2014 to 2016 in the First Affiliated Hospital of Chongqing Medical University (Chongqing, China) and the Research Institute of Surgery, Third Military Medical University (Chongqing, China). the qualified captured library of each sample was then loaded on Illumina HiSeq 2000 (Illumina, San Diego, CA) platforms and subjected to high-throughput sequencing.

  Dataset EGAD00001003224

• The molecular landscape of colorectal cancer reveals genetic mutations（5 cases）

  We collected tumor samples and adjacent nomal mucosae from 5 patients with colorectal cancer in surgical operation from 2014 to 2016 in the First Affiliated Hospital of Chongqing Medical University (Chongqing, China) and the Research Institute of Surgery, Third Military Medical University (Chongqing, China). the qualified captured library of each sample was then loaded on Illumina HiSeq 2000 (Illumina, San Diego, CA) platforms and subjected to high-throughput sequencing.

  Dataset EGAD00001003223

• Paired Biopsy Project: West Coast Dream Team

  This project aims to analyze the paired metastatic biopsy samples from patients with metastatic castration-resistant prostate cancer (mCRPC), collected before the initiation of the first-line androgen receptor signaling inhibitor (ARSI) for mCRPC and after radiographic disease progression on that ARSI, to understand the resistance mechanisms. We generated both whole genome sequencing (WGS) and RNA-seq data on these samples. A majority of these samples have been deposited in the public domain along with prior publications, and this project contains the 16 WGS samples that have not yet been deposited.

  Study EGAS50000000327

• Analysis of DNA methylation in normal B cells and chronic lymphocytic leukemia

  Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes.As second study using these samples focued on evolution and resulting intra-tumor heterogeneity in CLL. We used 450k bead-chip arrays to study DNA methylomes in 68 chronic lymphocytic leukemia (CLL) cases, including 28 serial cases. The result establishs linked evolution of epigenetic and genetic alterations in progressive disease, revealing an important aspect of the biology of epigenetics in cancer.

  Study EGAS00001000534

• The genetic footprint of the European Roma diaspora: Evidence from the Balkans to the Iberian Peninsula

  Our genomic approach focuses on: (i) the internal genetic structure of Roma and its correlation with geography; (ii) the relationships between Iberian Roma and other non-Roma populations to explore possible contacts during the period of population upheaval following the Roma’s arrival on the Iberian Peninsula; (iii) estimation of the admixture events in the Iberian Roma before and after their arrival to the Iberian Peninsula; and (iv) the assessment of endogamy patterns and assortative mating of the European Roma. Our study provides a detailed analysis of the intricate population history of the Iberian Roma, offering insights from both micro-geographical and large-scale perspectives on the population history of European Roma.

  Study EGAS50000000746

• Dataset for identification of the dismal subtype of B-ALL with dysregulation of CDX2 and UBTF

  WGS (tumor and germline samples) was performed to identify structural variants in the UBTF/CDX2 subgroup. RNA-seq was performed to detect gene fusion in the UBTF/CDX2 subgroup. HiChIP was performed to investigate 3D chromatin architecture and enhancer landscapes of representative patient samples and cell lines harboring Type I and II FLT3-PAN3 deletions and amplifications.

  Dataset EGAD00001008416

• Spatial Profiling Reveals Resistance in HER2+ Gastric Cancer

  HER2-positive gastric cancer (HER2+ GC) exhibits significant intra-tumoral heterogeneity and frequent development of resistance to HER2-targeted therapies. This study aimed to characterize the spatial tumor microenvironment (TME) and identify mechanisms of resistance to HER2 blockade including trastuzumab and trastuzumab deruxtecan (T-DXd) in HER2+ GC, with the goal of informing novel therapeutic strategies. We performed spatial transcriptomics on pre- and post-treatment samples from patients with HER2+ metastatic GC who received trastuzumab-based therapy.

  Dataset EGAD50000000898

• Whole genome sequencing of metastatic melanomas from a patient with primary resistance to BRAF inhibition

  Here, we investigated the underlying cause of treatment failure in a patient with BRAF mutant melanoma who presented primary resistance. We used whole-genome sequencing (WGS) to characterise five metastatic tumours from a BRAF mutant melanoma patient who presented intrinsic resistance.

  Study EGAS00001000580

• Genomic analysis of primary plasma cell leukemia reveals complex structural alterations and high risk mutational patterns

  Primary plasma cell leukemia (pPCL) is a rare and aggressive form of multiple myeloma (MM) that is characterized by poor overall survival despite advances in anti-MM therapy. The disease biology as well as molecular mechanisms that distinguish pPCL from non-pPCL MM remain poorly understood. In an attempt to identify key biological mechanisms that result in the aggressive pPCL phenotype we performed whole exome sequencing in 23 patients with newly diagnosed pPCL. The results reveal an enrichment of complex structural changes and high risk mutational patterns in pPCL that explain, at least in part, the aggressive nature of the disease. In particular pPCL patients with traditional low risk features such as translocation t(11;14) or hyperdiploidy accumulated adverse risk genetic events that could account for the poor outcome in this group.

  Study phs002022

• RNA bam files of Renal Cell Carcinoma patients

  the dataset contains RNA bam files of Renal Cell Carcinoma patients, which belongs to "An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors"

  Dataset EGAD00001003895

• Transposome Bisulfite Sequencing

  DNA belonging to 16 tumour/normal samples were treated with bisulfite, then up to 5 different bisulfite PCRs were performed in each one of the samples. Amplicons form the same sample were pooled and submitted to sequencing on a MiSeq platform.

  Dataset EGAD00001001028

• A Machine Learning Tool Integrating Circulating Cell-Free DNA Methylation with Clinical Variables for Non-Invasive Diagnosis of Liver Graft Pathology

  Liver Transplant Recipients (LTRs) with elevated liver enzymes can develop graft injury due to various etiologies, such as T-cell mediated rejection (TCMR) and NASH (NASH-LT). While liver biopsy is the gold standard method for diagnosis of graft pathology, it is invasive and is associated with risks. The goal of our study was to develop a Machine Learning (ML) tool integrating clinical variables with methylation patterns on circulating DNA in plasma as a non-invasive diagnostic tool of graft injury. We generated methylation profiles of circulating DNA in a pilot study of 43 LTRs (11 NASH-LT, 19 TCMR, and 13 Control-LT), and developed an L2 multinomial logistic regression ML approach across 101 bootstrapped models to distinguish between the graft conditions. NASH was associated with distinctive methylation patterns on genes involved in fatty acid metabolism, while methylation of platelet-derived growth factors was identified in patients with TCMR. Our ML model achieved a mean multi-classification accuracy of 0.91, with mean specificity and sensitivity of 0.94 and 0.91, respectively. The model was found to be particularly adept at detecting TCMR and Control-LT, with true positive rates (TPRs) of 95% and 90%, and areas under the curve (AUROC) of 0.992 and 0.985, respectively. For NASH-LT, the models achieved a performance with a TPR of 82% and an AUROC of 0.991. These preliminary results suggest that our newly developed ML tool, leveraging cell-free DNA methylation and clinical variables, is a promising non-invasive classifier of graft pathology.

  Study EGAS00001007171

• Germline hypomorphic CARD11 mutations in severe atopic disease

  We described five patients from four unrelated families who had severe atopic dermatitis and susceptibility to mild skin viral infections. Some patients also exhibited other allergic symptoms such as asthma and food allergy. We performed targeted sequencing for affected patients A-I of family A and B-I of family B, whole exome sequencing for D-I, D-II.1 and healthy mother D-II.3 of family D, and whole genome sequencing for C-I and healthy mother C-II.2 of family C. We identified three different novel damaging missense mutations of CARD11 (GeneID:84433) in patients A-I (L194P), B-I (R975W), and C-I (E57D). In patients D-I and D-II.1, a dup183_196 (p.K196_V197insMKEERDSYNDELVK) mutation was found in the coil-coil domain of the protein. These mutations act as dominant negatives impeding the scaffolding function of the wild type protein, which leads to downstream NF-kB and mTORC1 signaling defects after TCR stimulation. Sanger sequencing later identified the corresponding CARD11 mutations in the affected family members (C-II.1, D-II.2) that are not included in the dbGaP submission. Hypomorphic CARD11 dominant negative mutants are novel causes of severe atopic disease.

  Study phs001369