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• The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

  Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

  Study EGAS00001004518

• Nanopore_and_Illumina_sequencing_of_human_glioblastomas

  Liquid biopsy analysis refers to methods designed to detect tumour-specific material (e.g., circulating tumour cells or tumour DNA) in body fluids, such as urine or blood samples. A widely-used liquid biopsy approach consists of genotyping the circulating tumour DNA (ctDNA) through sequencing of plasma/serum DNA. Although useful in the context of metastatic disease (where the concentration of ctDNA is high), current liquid biopsy technologies show limited sensitivity of detection for the early detection of cancer, and low specificity, as cancer-related mutations accumulate in healthy tissues as part of the ageing process, thus making it difficult to distinguish these from tumour mutations, and because sequencing errors and true mutations show overlapping profiles. Therefore, developing liquid biopsy protocols with increased sensitivity and specificity represents an urgent clinical need. Here we harness extrachromosomal circular DNA (eccDNA) elements, which are circular DNA structures physically separated from the chromosomes of up to several Mbp long pervasive in human cancers, for liquid biopsy analysis. In this pilot study we will focus on the analysis of glioblastomas, because there is strong evidence for the presence of eccDNA in these tumour types, and because developing liquid biopsy approaches for brain tumours to reduce the invasiveness of brain tumour biopsies remains an unmet clinical need.

  Study EGAS00001005812

• Proteogenomics of chronic lymphocytic leukemia

  Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterized the proteome and transcriptome in-depth alongside genetic and ex-vivo drug response profiling in a clinically well annotated CLL discovery cohort (n= 68). Unsupervised clustering of the proteome data revealed six subgroups. Five of these proteomic groups were associated with genetic features, while one group was only detectable at the proteome level. This new group was characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). We developed classifiers to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n= 165, n= 169) and confirmed that ASB-CLL comprises about 20 % of CLL patients. The inferior overall survival observed in ASB-CLL was independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling. This is the transcriptomics data of the discovery cohort.

  Study EGAS00001005746

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma___2

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003542

• Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

  Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

  Dataset EGAD00001006231

• NIPT samples for systematic evaluation of NIPT aneuploidy detection software tools

  This dataset contains two sets of samples. The reference sample set consists of a total of 669 samples that had been reported previously to be euploid by the NIPTIFY screening test. The validation sample set is based on a previously published validation study by Zilina et al. (1), consisting of 423 samples, of which 259 were high-risk pregnancies that had undergone diagnostic invasive prenatal analysis (1). All samples were sequenced with Illumina NextSeq 500 platform, producing 85 bp single-end reads with an average per-sample coverage of 0.32× at the University of Tartu, Institute of Genomics Core Facility, according to the manufacturer’s standard protocols, as described previously (1). This study was performed with the approval of the Research Ethics Committee of the University of Tartu (#315/T-13). 1. Zilina O, Rekker K, Kaplinski L, Sauk M, Paluoja P, Teder H, et al. Creating basis for introducing non‐invasive prenatal testing in the Estonian public health setting. Prenat Diagn [Internet]. 2019 Dec 6;39(13):1262-8. Available from: https://onlinelibrary.wiley.com/doi/abs/10.1002/pd.5578

  Dataset EGAD00001007712

• Genetic drivers of epigenetic and transcriptional variation of human immune responses to infection (RNA-seq, ATAC-seq and ChIPmentation)

  RNA-seq, ATAC-seq and ChIPmentation data from monocyte-derived macrophages that were infected with Influenza A virus strain PR8WT, or a matching non-infected control.

  Dataset EGAD00001008422

• Single cell transcriptomic landscape of pediatric B-cell acute lymphoblastic leukemia: dissection of transcriptional heterogeneity and B-cell developmental state

  Introduction: Genomic analyses of bulk ALL samples have improved our understanding of the genetic basis and risk stratification of B-ALL, but do not directly examine intratumor heterogeneity or enable inference of leukemia developmental state and cell of origin. Methods: We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) (10X Genomics 5’v2) and compared them to a scRNA-seq reference map of normal human B-cell development. Results: Analysis of heterogeneity of inferred DNA copy number alterations at single cell level showed that aneuploid ALL with near haploidy and hyperdiploid harbor chromosomal losses or gains in all blasts, consistent with early, synchronous origin rather than sequential accumulation. Intra-sample heterogeneity was driven by five gene expression signatures: cell cycle, metabolism, differentiation, inflammation, refining leukemic subtyping. An atlas of B cell development was established to map B-ALL samples to specific developmental states. Hyperdiploid samples resembled pro-B cells, while MEF2D-r and TCF3::PBX1 showed high pre-B abundance. Patients with high early lymphoid abundance had poorer outcomes. Conclusions: Understanding variation in transcriptional programs and developmental states of B-ALL blasts by sc transcriptome refines existing clinical and genomic classifications and provides novel prognostic markers.

  Study EGAS00001007512

• Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors

  Extensive molecular analysis by many groups has revealed a heterogeneous landscape of embryonal brain tumors, including medulloblastoma (MB) and atypical teratoid/rhabdoid tumor (ATRT). MB, the most common malignant pediatric brain tumor, is comprised of four molecularly distinct subgroups: Wingless (WNT), Sonic Hedgehog (SHH), Group 3 (G3), and Group 4 (G4). Among these, MB-SHH harboring MYCN amplification and TP53 mutation and MB-G3 with MYC overexpression or amplification constitute the most aggressive tumors, have the poorest clinical outcomes, and lack effective therapeutic options for recurrent disease. Here we describe the establishment of tumor organoid (TO) models from patient-derived orthotopic xenografts (PDOX) of MYCN-amplified and TP53-mutant MB-SHH, MYC-amplified MB-G3 and two ATRT which all grew in mice when reimplanted into the cortices of naïve recipient animals (TOX). Methylation, bulk and single-cell RNA sequencing, and whole genome sequencing demonstrated that TOs and TOXs faithfully recapitulated the molecular landscape and heterogeneity of PDOXs and primary patient tumors compared to established cell lines. The development of TOs will facilitate in vitro high-throughput drug or CRISPR screens without the need for use tumor-bearing mice. This will also accelerate the identification and validation of new vulnerabilities and in vivo preclinical testing toward clinical trials.

  Study EGAS00001008305

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001002608

• Caregiving as a Natural Stressor in Studies of the Role of Genes That Affect Serotonin Function in Regulating Risk Factors for Coronary Heart Disease (CAREGIVER)

  The burden of caregiving for an ill relative has been shown to interact with existing comorbidities to increase risk of several health outcomes including metabolic syndrome and blood pressure reactivity. The CAREGIVER study was developed to compare cardiometabolic risk factors in caregivers and controls. These risk factors include physiologic measures, psychologic measures, neighborhood characteristics, and genetic and genomic factors. DNA and plasma were collected and used for examination of cardiometabolic and stress biomarkers, genotyping and methylation analysis.

  Study phs001747

• scRNA-seq of human follicular lymphoma and lymph node

  Cryopreserved cells from human nodal follicular lymphoma and lymph node samples were thawed and processed for scRNA-seq analysis. CD3+ CD19− 7-AAD− live T cells (six FL samples from the Original cohort) or 7-AAD− whole live hematopoietic cells (five lymph node and nine FL samples from Validation cohort 1) were sorted using a FACS Aria II or III instrument (BD Biosciences). To generate single-cell emulsions, 6,000–10,000 live cells were loaded into the 10X Genomics Chromium Controller for single-cell partitioning, along with the reverse transcriptase reagent mixture and 3' or 5' gel beads. Sorted T or whole hematopoietic cells were converted to barcoded scRNA-seq libraries using 10X Genomics Chromium single cell 3' reagent kits (v3) for the Validation cohort 1, 5' reagent kits (v1) for the Original cohort, according to the manufacturer’s instructions. The libraries were sequenced on an Illumina HiSeq X Ten or NovaSeq X Plus system, mapped to the human genome (build GRCh38), and demultiplexed using CellRanger pipelines (v3.1.0, 10x Genomics).

  Dataset EGAD50000001143

• Characterization of a New Case of XMLV (Bxv1) Contamination in the Human Cell Line Hep2 (Clone 2B) Using High-Throughput DNA- and RNA-Seq

  We have sequenced DNA and RNA from the Hep2 (clone 2B) cell line (Sigma-Aldrich catalog number: 85011412-1VL) using short read Illumina sequencing. We show that this cell line is indistinguishable from the HeLa cell line (as mentioned on the Sigma-Aldrich website) by mapping integrations of the human papillomavirus 18. We also show that the cell line is contaminated by the Bxv1 xenotropic murine leukemia virus. This contamination has to be taken into account when using the cell line in future experiments.

  Study phs001944

• 16S rRNA gene V4 region sequencing data, ASV profiles, and sample metadata of human faecal samples predominantly from the Estonian population

  This dataset comprises 16S rRNA gene V4 region amplicon sequencing data generated from 1,826 human faecal samples, predominantly from the Estonian population. The dataset includes raw sequencing reads and processed amplicon sequence variant (ASV) outputs, consisting of ASV abundance tables, representative ASV sequences, and taxonomic assignments. In addition, a sample metadata table is provided, containing sample and host information, including sample identifier, sequencing run identifier, date of sampling, sex, age, height, weight, nationality, disease status, and Bristol stool type. Sequencing was performed using the Illumina MiSeq and iSeq 100 platforms. The cohort includes individuals with no reported disease (n = 889), gastrointestinal diseases (n = 217), allergies and asthma (n = 194), thyroid gland disorders (n = 117), cardiovascular diseases (n = 103), various general health conditions (n = 139), cancer (n = 28), diabetes (n = 20), gynaecological issues (n = 7). Disease status was unavailable for 112 samples.

  Dataset EGAD50000002306

• Impact of Mutated CTCF DNA binding sites of Topologically associating domains on nearby Cancer Gene Regulation: A Multi-Omics Analysis

  Cutaneous squamous cell carcinoma (cSCC) is the most common lethal malignancy world-wide. Due in most part to the extremely high mutational burden (TMB) in cSCC, making sense of it’s non-coding and regulatory regional genomic variation has lagged that of other far less common cancers. This study presents the first investigation of mutations at CCCTC-binding factor binding sites (CTCFbs) of Topologically associating domains (TAD) across defined cSCC progression stages—primary non-metastatic (PNM), primary metastat-ic (PM), and lymph node metastasis (LNM).

  Study EGAS50000001686

• Identification of fusion transcripts by RNA-sequencing and Whole genome sequencing of a METABRIC patient sample

  Fusion transcripts and their exact breakpoints were identified in RNA-seq data (30X) of an ER-,HER2+ breast cancer. DNA-level breakpoints associated with the fusion events were determined by analyzing whole genome sequencing (WGS) data (30X) from the same donor. The RNA-seq and WGS data for this case were generated on the Illumina platform using standard protocols. The patient (MB-0152) derives from the METABRIC cohort for which array based copy number and gene expression data were previously described (EGAS00000000083).

  Study EGAS00001002475

• RUNX1 mutated families show phenotype heterogeneity and a somatic mutation profile unique to germline predisposed AML

  We present the clinical phenotypes and genetic mutations detected in 10 novel RUNX1 mutated FPD-MM families. Genomic analyses on these families detected two partial gene deletions, three novel mutations and five recurrent mutations as the germline RUNX1 alterations leading to FPD-MM. On 15 individuals, across the 10 families, we performed additional whole exome or myeloid panel sequencing on blood or bone marrow to determine somatic mutations that co-exist with the germline RUNX1 mutation in tumour and pre-leukaemic states.

  Study EGAS00001004273

• FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

  FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls. The POP study placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater (ThermoFisher). For each biopsy, total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. RNA-libraries were prepared from 1g of total placental RNA with the TruSeq Stranded mRNA Library Prep Kit (Illumina) which captures polyA-tailed transcripts by oligo-dT beads, then pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and Illumina HiSeq2500

  Dataset EGAD00001006304

• Lenalidomide Resistance in del(5q) Myelodysplastic Syndrome Follows Loss of RUNX1/TP53-mediated Megakaryocytic Differentiation

  Interstitial deletion of the long arm of chromosome 5 (del(5q)) is the commonest structural genomic variant in myelodysplastic syndromes (MDS). Lenalidomide (LEN) is the treatment of choice for patients with del(5q) MDS, but half of the responding patients become resistant within two years. TP53 mutations are detected in ~20% of patients who become resistant to LEN. Our data show that patients who become resistant to LEN harbor either TP53 or RUNX1 mutations or loss of RUNX1 expression. Here we show that LEN-induced degradation of IKZF1 permits a RUNX1/GATA2 complex to drive megakaryocytic differentiation and consequent del(5q) MDS progenitor cell death via CRBN-mediated CSNK1A1 degradation. Overexpression of GATA2 is able to restore LEN sensitivity in the context of RUNX1 or TP53 mutations by enhancing LEN-induced megakaryocytic differentiation. Screening for TP53 and RUNX1 mutations or downregulation should identify patients resistant to LEN, and strategies to activate GATA2 may resensitize del(5q) MDS cells to LEN.

  Dataset EGAD00001005769

• WGS dataset of Characterization of UV DNA damage in B-cell precursor acute lymphoblastic leukemia

  We characterized B-cell precursor acute lymphoblastic leukemia (BCP-ALL) patients that present with the mutational signature SBS7a. We found clear subtype specificity, but presence of SBS7a did not seem linked to heterogeneity within subtypes. To further distinguish the incidence of SBS7a in pediatric cancer we analyzed a pan-cancer WGS cohort and identified frequent SBS7a in anaplastic large cell lymphomas. As SBS7a is commonly found in skin cancers and has been linked to UV-light induced DNA damage, we compared the features of UV-light induced DNA damage in skin cancer and SBS7a in ALL, and found high similarity. We found no defects in UV damage response pathways in SBS7a-positive samples, indicating no additional UV vulnerability. Additionally, transcriptomic data showed no differences between samples with and without SBS7a. Finally we looked into the moment of exposure to the source of SBS7a by deep sequencing of diagnosis-relapse pairs and single cell whole genome sequencing of diagnosis samples with high SBS7a.

  Dataset EGAD00001015600

• WES data

  WES FASTq files of 76 bulk pre-treatment tumors and 76 matched peripheral blood mononuclear cells from GO30140 group A

  Dataset EGAD00001008129

• Whole exome sequencing of non-small cell lung cancer patient-derived xenografts

  Non-small cell lung cancer (NSCLC) is the leading cause of cancer deaths worldwide. Only a fraction of NSCLC harbour actionable driver mutations and there is an urgent need for patient-derived model systems that will enable the development of new targeted therapies. We generated NSCLC patient-derived xenografts (PDXs) that recapitulate the histology and molecular features of primary NSCLC. Here, we completed whole exome sequencing on 122 NSCLC PDXs.

  Dataset EGAD00001008601

• Tagged-amplicon deep sequencing

  This dataset contains a collection of tumour samples from high grade serous ovarian carcinoma patients with recurrent disease collected near the point of diagnosis as well as tumour samples collected after patient relapse upon or some time after study entry. Whole blood samples were also collected from patients at study entry for the purpose of germline variant detection. The majority of diagnosis samples were preserved in neutral buffered formalin whereas the majority of post-relapse samples were preserved in universal molecular fixative (UMFIX, Sakura Finetek USA, Inc). DNA was extracted and the tagged-amplicon deep sequencing assay was applied (TAm-Seq, Forshew et al. 2002, Sci Transl Med) with the aid of fluidigm access array technology. Targeted loci were sequenced at very high depths (typically >100X) for the detection of both somatic and germline variants. Sequenced reads were aligned to the GRCh37 reference genome (release hs37d5).

  Dataset EGAD00001011058

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• The ALT pathway generates telomere fusions that can be detected in the blood of cancer patients

  Telomere fusions (TFs) can trigger the accumulation of oncogenic alterations leading to malignant transformation and drug resistance. Despite their relevance in tumour evolution, our understanding of the patterns and consequences of TFs in human cancers remains limited. Here, we characterize the rates and spectrum of somatic TFs across >30 cancer types using whole-genome sequencing data. TFs are pervasive in human tumours with rates varying markedly across and within cancer types. In addition to end-to-end fusions, we find novel patterns of TFs that we mechanistically link to the activity of the alternative lengthening of telomeres (ALT) pathway. We show that TFs can be detected in the blood of cancer patients, which enables cancer detection with high specificity and sensitivity even for early-stage tumours and cancers of high unmet clinical need. Overall, we report a novel genomic footprint that enables characterization of the telomere maintenance mechanism of tumours and liquid biopsy analysis.

  Dataset EGAD00001012101