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• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• Undifferentiated sarcomas develop through distinct evolutionary pathways

  Undifferentiated sarcomas (USARC) of adults are diverse, rare and aggressive soft tissue cancers. Recent efforts have confirmed that USARC exhibit one of the highest burdens of structural aberrations across human cancer. Here, we sought to unravel the genomic basis of this structural complexity by integrating whole genome sequencing, ploidy analysis and methylation profiling of 53 USARC. We identified whole genome doubling as a prevalent and pernicious force in USARC tumourigenesis. Deconvolution of the complex copy number and rearrangement landscapes show distinct signatures associated with chromothripsis, early-haploidy, and successive whole-genome-doubling events, suggesting four divergent models of sarcoma development. We show similar distinct evolutionary tumourigenic pathways in different sarcoma subtypes from the Cancer Genome Atlas. Thirteen percent of tumours exhibited a hypermutator phenotype, opening new avenues for clinical management such as immunotherapy, whilst the period prior to and between genome doubling events may represent clinically relevant interventional points in USARC.

  Dataset EGAD00001004162

• NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III - Brazil Sickle Cell Disease Cohort (REDS-BSCDC)

  The Recipient Epidemiology and Donor Evaluation Study (REDS)-III program established a Brazilian Sickle Cell Disease (SCD) Cohort to identify molecular determinants of response to transfusions, alloimmunization and risk factors associated with HIV infection. The Brazil population presents a complex admixture of African, European, Asian and Indigenous heritage and will provide insights into genetic, demographic, social, and healthcare system determinates of SCD outcomes. The REDS-III Brazil SCD cohort began in the Fall of 2013 and aimed to: Establish a cohort of SCD patients with a comprehensive centralized electronic database of detailed clinical, laboratory and transfusion information, as well as establish a repository of blood samples to support biological studies relevant to SCD pathogenesis and transfusion complications; Characterize changes in markers of inflammation in response to transfusion by analyzing chemokine/cytokine panels in serial post transfusion specimens; Identify single nucleotide polymorphisms (SNPs) that contribute to the risk of red blood cell alloimmunization in SCD by performing a genome-wide association (GWA) study in transfused SCD patients; Characterize risk of HIV and HIV outcomes in the Brazilian SCD population and compare SCD outcomes among HIV sero-positive and sero-negative SCD patients.

  Study phs001972

• Spatial_transcriptome_analysis_of_Paediatric_Thymus

  Cell atlas of Paediatric Thymus Cell atlas of Paediatric Thymus - The Human Cell Atlas initiative is an ambitious global research effort which aims to describe every cell in the human body across all developmental stages to generate a reference map to accelerate progress in science and medicine particularly relating to human development and disease. The initiative is led by investigators based at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and funding support from the Wellcome and NIH. We aim to interrogate the cellular composition and molecular regulators underpinning a cells identity through; genetic and genomic analysis, expression analysis, non-identifiable video imaging and cell line and organoid production, as well as, computational algorithms to predict cellular developmental trajectories and cell-cell interactions. We will subsequently validate these findings in situ using spatial genomic and imaging technologies e.g. immunohistochemistry, RNAscope, in situ sequencing and spatial transcriptomic analyses. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001004281

• The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: Defining a Healthy Volunteer Cohort

  The integration of comprehensive genomic and phenotypic data from diverse ethnic populations offers unprecedented opportunities towards advancements in precision medicine and novel diagnostic technologies. Current reference genomic databases are not representative of the global human population, making variant interpretation challenging, especially in underrepresented populations such as the North African population. To address this, the Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project launched a study comprising 1000 individuals free of cardiovascular disease (CVD). Here, we present the first 391 Egyptian healthy volunteers (EHVols) recruited to establish a pilot phenotyped control cohort. All individuals underwent detailed clinical investigation, including cardiac MRI, and were sequenced using a targeted panel of 174 genes with reported roles in inherited cardiac conditions (ICC). We identified 1,262 variants in 27 cardiomyopathy genes of which 15.1% were not captured in current global and regional genetic reference databases (here: gnomAD and Great Middle Eastern (GME) Variome). The ECCO-GEN project aims at defining the genetic landscape of an understudied population and providing individual-level genetic and phenotypic data to support future studies in CVD and population genetics.

  Study EGAS00001004434

• Patient-derived neuroblastoma model system OHC-NB1

  Accurate disease modeling presents a bottleneck against effective translation of novel neuroblastoma therapies into the clinic. Recently, considerable intra-tumor genetic heterogeneity has been observed in neuroblastoma, which calls for preclinical models that reflect this feature. Flexibility in a testing platform is also desirable to support assessment of different endpoints and tumor cell characteristics. We present the novel neuroblastoma model OHC-NB1, propagated from a bone marrow metastasis from a patient with INRG stage M, MYCN-amplified neuroblastoma at first diagnosis. To model different aspects of the disease, several preclinical models were developed from the bone marrow aspirate: a tissue plastic-adherent cell line, a 3-dimensional (3D) spheroid culture, and cell line-derived xenografts that were subcutaneously passaged in mice. Typical aspects of MYCN-amplified neuroblastoma, such as MYCN amplification in double minutes, 1p deletion, 17q gain, and a diploid karyotype, are present in OHC-NB1 and persist in all culture types. Whole exome sequencing revealed intra-tumor heterogeneity in the bone marrow metastasis reflected in the culture models. The set of OHC-NB1 cultures with a genetically heterogeneous MYCN-amplified neuroblastoma background provide a flexible preclinical testing system that recapitulates important features of metastatic neuroblastoma.

  Study EGAS00001003031

• Functional single-cell characterization of immune aplastic anemia shows convergence of NK and NK-like CD8+ T cells with disease-associated TCR signature

  Immune aplastic anemia (AA) is a life-threatening bone marrow (BM) failure disorder driven by an autoimmune T cell attack against the hematopoietic stem and progenitor cells (HSPCs). However, the autoantigen targets and the role of other immune cells are unknown. Here, by analyzing an international cohort of 156 AA patients with scRNA+TCRαβ-seq, TCRβ-seq, flow cytometry, and plasma cytokine profiling with comparisons to healthy controls and patients with other hematological disorders, we identify NK cells and CD8+ TEMRA cells expressing NK receptors with AA-associated TCRβ-seq motifs as the most dysregulated immune cell populations in AA BM. Functional co-culture experiments with scRNA-TCRαβ-seq readout utilizing primary HSPCs and immune cells provide evidence that NK cellscannot kill HSPCs alone, but sensitize them to CD8+ T cell-mediated killing. Furthermore, HSPCs induce strong activation of T cell clones with CD8+ TEMRA NK-like phenotype and AA-associated TCR motifs. Our results reveal the convergent evolution of innate and adaptive immune cells in AA, where NK cells support CD8+ T cell-mediated autoimmunity.

  Study EGAS00001007602

• Functional single-cell characterization of immune aplastic anemia shows convergence of NK and NK-like CD8+ T cells with disease-associated TCR signature

  Immune aplastic anemia (AA) is a life-threatening bone marrow (BM) failure disorder driven by an autoimmune T cell attack against the hematopoietic stem and progenitor cells (HSPCs). However, the autoantigen targets and the role of other immune cells are unknown. Here, by analyzing an international cohort of 156 AA patients with scRNA+TCRαβ-seq, TCRβ-seq, flow cytometry, and plasma cytokine profiling with comparisons to healthy controls and patients with other hematological disorders, we identify NK cells and CD8+ TEMRA cells expressing NK receptors with AA-associated TCRβ-seq motifs as the most dysregulated immune cell populations in AA BM. Functional co-culture experiments with scRNA-TCRαβ-seq readout utilizing primary HSPCs and immune cells provide evidence that NK cellscannot kill HSPCs alone, but sensitize them to CD8+ T cell-mediated killing. Furthermore, HSPCs induce strong activation of T cell clones with CD8+ TEMRA NK-like phenotype and AA-associated TCR motifs. Our results reveal the convergent evolution of innate and adaptive immune cells in AA, where NK cells support CD8+ T cell-mediated autoimmunity.

  Study EGAS00001007604

• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588