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• Coding and small non-coding transcriptional landscape of tuberous sclerosis complex cortical tubers: implications for pathophysiology and treatment

  Tuberous Sclerosis Complex (TSC) is a rare genetic disorder that results from a mutation in the TSC1 or TSC2 genes leading to constitutive activation of the mechanistic target of rapamycin complex 1 (mTORC1). TSC is associated with autism, intellectual disability and severe epilepsy. Cortical tubers are believed to represent the neuropathological substrates of these disabling manifestations in TSC. In the presented study we used high-throughput RNA sequencing in combination with systems-based computational approaches to investigate the complexity of the TSC molecular network. Overall we detected 438 differentially expressed genes and 991 differentially expressed small non-coding RNAs in cortical tubers compared to autopsy control brain tissue. We observed increased expression of genes associated with inflammatory, innate and adaptive immune responses. In contrast, we observed a down-regulation of genes associated with neurogenesis and glutamate receptor signaling. MicroRNAs represented the largest class of over-expressed small non-coding RNA species in tubers. In particular, our analysis revealed that the miR-34 family (including miR-34a, miR-34b and miR-34c) was significantly over-expressed. Functional studies demonstrated the ability of miR-34b to modulate neurite outgrowth in mouse primary hippocampal neuronal cultures. This study provides new insights into the TSC transcriptomic network along with the identification of potential new treatment targets.

  Study EGAS00001002485

• ICGC Prostate Cancer Whole Genome Sequencing

  To characterize the subclonal genomic architecture of androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of 51 tumours from 10 patients to an average sequencing depth of 55x, including multiple metastases from different anatomic sites in each patient and, in five cases, the prostate tumour. Noncancerous DNA from blood or other tissue is used as reference comparison for each patient. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) rapid autopsy study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, some of the studies using these data include: Gundem et al, Nature 2015 (PMID: 25830880). Additional EGAD00001000891 sample metadata is contained in Supplementary Information in this report.Tubio et al, Science 2014 (PMID: 25082706) Behjati et al, Nature Comm 2015 (PMID: 27615322) Wedge et al, Nature Genetics 2018 (PMID: 29662167)Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)Rodriguez-Martin et al, Nature Genetics 2020 (PMID: 32024998)Woodcock et al, Nature Comm 2020 (In Press)

  Dataset EGAD00001000891

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  We generated a dataset consisting of 79 VCF files, and respective FASTQ and CRAM files, methodically generated using the GLIMPSE1 imputation algorithm leveraging the 1000 Genomes Project Phase 3 dataset as the reference panel of haplotypes. In total this dataset is composed of approximately 325 GB of FASTQ data, 156 GB of CRAM data, and 6 GB of VCF data. Our samples were specifically derived from sequenced DNA from a highly selective cohort of patients, mostly comprised of Iberian Populations in Spain (IBS) individuals but also containing some individuals with other genetic backgrounds, who presented severe COVID-19 symptoms during the initial wave of the SARS-CoV-2 pandemic in Madrid, Spain. On average, each VCF file in this rich dataset contains 9.49 million high-confidence single nucleotide variants [95%CI: 9.37 million - 9.61 million].

  Dataset EGAD00001011363

• Sequencing probands and families with severe insulin resistance syndromes

  This is an ongoing project and continuation to all the sequencing we have been doing over the last few years. We have some additional families and probands with syndromes of insulin resistance not previously sequenced within uk10k or other core funded projects. We would like to complete the sequencing in all of the good quality families and probands we have, this would require another ~50 samples to be WES sequenced. This cohort has already proven to be a rich source of interesting findings with papers in Science and Nature genetics.

  Dataset EGAD00001000694

• Exploiting evolutionary steering in cancer therapy

  Drug resistance, mediated by intra-tumour heterogeneity and clonal evolution, is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at the cost of increased sensitivity to another due to so-called evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, model systems able to recapitulate cancer evolution experimentally are lacking and current in vitro techniques based on small populations, re-plating and escalating dose, are unsuitable to develop evolutionary herding strategies. We present a novel methodology for evolutionary herding in vitro and ex vivo using patient-derived organoids. Our approach is based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, realistic high drug doses, time-course monitoring of cancer clones, and mathematical modelling of tumour evolutionary dynamics. We demonstrate evolutionary herding in non-small cell lung cancer in vitro and in patient-derived colorectal cancer organoids (PDO). We show that herding causes controlled evolutionary bottlenecks that lead to collateral sensitivity. Through genomic analysis, we were also able to determine the mechanisms that drive such sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can be translated into the clinic to control treatment resistance.

  Study EGAS00001003200

• Genome-Wide Association Study of Endometrial Cancer in the Epidemiology of Endometrial Cancer Consortium (E2C2)

  Endometrial cancer, the most common gynecological malignancy in the United States, has both an environmental and genetic component. To this end, we conducted a genome-wide association study to identify genes involved in endometrial cancer using studies from the NCI-supported Epidemiology of Endometrial Cancer Consortium (E2C2). For the discovery stage we included samples from 6 cohort and 7 case control studies through 2007. The total number of cases genotyped were 2,307, white women of European descent, and 2,307 matched controls using the Illumina HumanOmniExpress platform. We conducted the replication using the Infinium HumanExome BeadChip, which successfully genotyped 177,139 variants in 1055 cases and 1778 controls from four ethnically diverse studies that are part of the Epidemiology of Endometrial Cancer Consortium (E2C2). The overall goal is to determine whether certain genotypes are predictive of future endometrial cancer risk, and whether the genotypes interact with established endometrial risk factors.

  Study phs000893

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers: multi-timepoint exome sequencing of a single patient's disease

  This dataset is a time-series of EGFR-mutant NSCLC clinical specimens from an individual patient profiled using tumor-based whole exome sequencing and the data is in BAM format. DNA was extracted from FFPE for primary tumor and frozen tumor tissue samples and matched non-tumor tissue using the Qiagen Allprep DNA/RNA Mini Kit.  The library preparation protocol was based on the Agilent SureSelect Library Prep and Capture System. DNA was resuspended in a low TE buffer and sheared (Duty Cycle 5%; Intensity 175; Cycles/Burst: 200; Time: 300s, Corvaris S2 Utrasonicator).  Bar-coded exome libraries were prepared using the Agilent Sure Select V5 library kit per manfucaturer’s specifications. The libraries were run on the HiSeq2500. Raw paired end reads (100bp) in FastQ format generated by the Illumina pipeline were aligned to the full hg19 genomic assembly obtained from USCS, gencode 14, using bwa version 0.7.12. Picard tools version 1.117 was used to sort, remove duplicate reads and generate QC statistics. Tumor DNA was sequenced to median depth of 303X (range 114.39-383.41) and the matched germline DNA to average depth of 231.65.

  Dataset EGAD00001003769

• Screening Protocol and Longitudinal Study of Bone Marrow Failure Syndromes and Cytopenias

  The purpose of this study is to characterize patients with Bone Marrow Failure Syndromes (BMFS) and to track the clinical course of patients with these diseases over time. An exact and comprehensive diagnosis at presentation is essential. Due to the sporadic nature of BMFS (aplastic anemia, myelodysplastic syndrome, paroxysmal nocturnal hemoglobinuria, pure red cell aplasia, amegakaryocytic thrombocytopenic purpura and large granular lymphocyte leukemia) most diseases have not undergone systematic long-term outcome studies. Individual diseases, combined under the collective entity of bone marrow failure syndromes, frequently overlap and evolve from each other. The frequency of complications, associations with other diseases, and genetic factors such as allelic polymorphisms are not well studied. Some of these syndromes are likely mediated by the cellular immune system. However, while target antigens are likely to be expressed on early hematopoietic cells, their identification has been unsuccessful. Hypothesis: Clinical and epidemiologic studies may, through etiologic clues and intricate laboratory testing, facilitate the understanding of the pathophysiology of BMFS and ultimately lead to implementation of better diagnostic tools and more targeted and rational therapies.

  Study phs000592

• Multi-omics analysis defines core genomic alterations in pheochromocytomas and paragangliomas

  Pheochromocytomas (PCC) and paragangliomas (PGL) are neural crest-derived tumors. We performed the integrated genomic analysis of a collection of PCC/PGL from the French COMETE network using SNP arrays, whole-exome sequencing, DNA methylation arrays, mRNA expression arrays and miRNA sequencing. We found that PCC/PGL are characterized by a low mutation rate, with few recurrent somatic mutations and focal copy number alterations (CNAs). In contrast, we detected recurrent broad CNAs strongly associated with known molecular groups, often leading to the biallelic inactivation of the known susceptibility genes of PCC/PGL. We also identified DNA methylation changes and miRNA expression clusters strongly associated with molecular groups. Of note, overexpression of the miRNA cluster 182/96/183 is specific of SDHB-mutated tumors and induces invasive traits, whereas silencing of the imprinted DLK1-MEG3 miRNA cluster due to a loss of heterozygosity of the 14q32.2 locus is a potential driver in a subset of sporadic tumors. This comprehensive analysis illustrates the functional interdependence between genomic and epigenomic dysregulations underlying PCC/PGL.

  Study EGAS00001000933

• Comprehensive genomic profiles of small cell lung cancer

  We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. We found bi-allelic inactivation of TP53 and RB1 in nearly all the tumors analyzed, sometimes by complex genomic rearrangements. Two tumors with wild-type RB1 had evidence of chromothripsis leading to overexpression of Cyclin D1, revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumor suppressors TP53 and RB1 is obligatory in SCLC. We further discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Δex2/3. In few cases, SCLC tumors exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signaling in a pre-clinical SCLC mouse model dramatically reduced the number of tumors and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer.

  Study EGAS00001000925

• SARS‐CoV‐2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells

  The SARS‐CoV‐2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID‐19 pathogenesis, especially host factors facilitating virus infection and replication. SARS‐CoV‐2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is strongly expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS‐CoV‐2 infection. Our data provide a rich resource for future investigations of COVID‐19 infection and pathogenesis.

  Study EGAS00001004419

• T cell responses of ALS patients

  In this project, we aimed to understand how T cell responses contribute to the disease progression of amyotrophic lateral sclerosis (ALS). The present data is on single-cell sequencing isolated from human cerebrospinal fluid (CSF) cells from both ALS patients (n=5) and controls (n=4). This analysis was conducted as part of a bigger project which is summarized in the section below. We used flow cytometry to define T cell subsets and phenotypes in blood and CSF samples collected at the time of diagnosis on a cohort of 89 newly diagnosed ALS patients in Stockholm, Sweden. High frequency of CD4+FOXP3- effector T cells in blood and CSF was associated with poor survival whereas high frequency of activated regulatory T (Treg) cells and high ratio between activated and resting Treg cells in blood was associated with better survival. T cell profiles also predicted disease progression rate. On an independent cohort of cases and controls, we used single cell transcriptomics data to demonstrate that ALS patients had altered T cell gene expression patterns and clonally expanded CD4+ and CD8+ T cells in CSF. In summary, T cell responses contribute to disease progression of ALS, supporting modulation of adaptive immunity as a viable therapeutic option.

  Study EGAS00001006675

• Clinical and Genetic Analysis of Costa Rican Patients with Parkinson's Disease

  This study is a pilot study designed to describe the clinical and genetic landscape of Parkinson's disease in Costa Rica. While most genetic studies have been conducted on Europeans, few have examined Parkinson's disease in Costa Ricans. 118 patients and 97 controls were recruited at the Movement Disorders Unit of the Department of Neurology, Hospital San Juan de Dios, Caja Costarricense de Seguro Social, Costa Rica. Familial Parkinson's disease genes were sequenced using Next-Generation Sequencing. We also measured and obtained different sociodemographic and clinical information.

  Study phs002495

• 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

• A single-cell atlas of human glioma

  Although tumor-propagating cells can be derived from glioblastomas (GBMs) of the proneural and mesenchymal subtypes, a glioma stem-like cell (GSC) of the classical subtype has not been identified. It is unclear if mesenchymal GSCs (mGSCs) and/or proneural GSCs (pGSCs) alone are sufficient to generate the spectrum of cellular heterogeneity observed in GBM. This study sheds light on a long-standing debate regarding lineage relationships among GSCs.

  Study EGAS00001003845

• IBDCA_Edinburgh

  In this experiment we have sequenced tumour normal pairs from patients presenting with CRC who have a prior history of inflammatory bowel disease. The idea is to identify driver mutations, new genes and novel pathways associated with the development of these malignancies.

  Dataset EGAD00001001330

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• UK_ReplicationChip

  This dataset includes data from UK Multiple Sclerosis (MS) cases that were recruited through the University of Cambridge and included in the IMSGC Replicationchip experiment. Data from UK controls and additional UK cases that were recruited through other UK centres is available by direct application to those respective centres, as described in the original paper.

  Dataset EGAD00010002118

• UK_exomechip

  This dataset includes data from UK Multiple Sclerosis (MS) cases that were recruited through the University of Cambridge and included in the IMSGC exomechip experiment. Data from UK controls and additional UK cases that were recruited through other UK centres is available by direct application to those respective centres, as described in the original paper

  Dataset EGAD00010002019

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• Chronic Renal Insufficiency Cohort (CRIC) Study Metabolomics and Proteomics

  The Chronic Renal Insufficiency Cohort (CRIC study) was established in 2001 by the National Institute of Diabetes, Digestive, and Kidney Diseases (NIDDK) to improve the understanding of the relationship between chronic kidney disease and cardiovascular disease. The goals of the CRIC Study are to examine risk factors for progression of chronic kidney disease and cardiovascular disease among patients with chronic kidney disease and to develop predictive models to identify high-risk subgroups, informing future treatment trials and increasing application of available preventive therapies. This record includes plasma metabolomics and plasma proteomics data. Genotype data for 3527 CRIC Study partcipants is available at dbGaP in phs000524, "Chronic Renal Insufficiency Cohort (CRIC)-GWAS". Additional phenotypic, clinical, and outcomes data are available at the NIDDK Central Repository and can be linked to data available at dbGaP.More than 330 manuscripts have been published, reporting on the effects of a broad range of risk factors (from molecular biomarkers of disease pathways to clinical, demographic, and behavioral characteristics) on the progression of CKD and other health consequences. The full CRIC bibliography can be found at the BIBLIOGRAPHY for the Chronic Renal Insufficiency Cohort (CRIC) Study.

  Study phs003709

• Family-Based Study on Ulcerative Colitis with Whole Exome Sequencing

  Genetic risk factors for ulcerative colitis are not well understood. We performed a family-based whole exome sequencing analysis to identify potential causal mutations. In the proband, we found a heterozygous de novo mutation in the gene HSPA1L. Our results indicate that the de novo mutation in HSPA1L is associated with ulcerative colitis.

  Study phs001251

• The Nurses' Health Study (NHS) GWAS of Mammographic Density

  The Nurses' Health Study is an on-going prospective cohort study of women that was initiated in 1976. This specific study was part of a larger study to advance our knowledge of breast cancer etiology, expand the current knowledge of mammographic density, and clarify the relationship between mammographic density and breast cancer risk. We conducted a nested case control study of breast cancer among women who provided a blood sample. We then targeted our mammogram collection to participants that were selected as part of this nested case-control study (i.e. those who had provided a blood sample). The mammogram closest to the date of blood draw (~1989-1990) was used. We assessed mammographic breast density from digitized film images using a computer assisted thresholding method (Cumulus). The women in this study were genotyped using the Illumina Omni Express Platform.

  Study phs000975

• Transcriptomic profiling of granulosa cells from IVF patients at different ages

  Two major factors contributing to reduced fertility is use of exogenous hormones and old age. Here, we sequenced RNA from granulosa cell samples from human patients undergoing in vitro fertilization to test how hormonally stimulated cells' transcriptional profiles change with age. All patients were normal responders referred for male infertility and were grouped into two age groups. The gene expression differences in aging were compared to mouse data (previous experiments, see ArrayExpress E-MTAB-13479) and the results are published in the article "Granulosa cell transcription is similarly impacted by superovulation and aging and predicts early embryonic trajectories". Corresponding count tables are available in ArrayExpress (E-MTAB-13496).

  Study EGAS50000000824

• Personalized Treatment of Sezary Syndrome through a CTLA4:CD28 Fusion

  We sequenced two tumor and one normal whole genome libraries for a Sezary syndrome patient and also sequenced RNA libraries for each tumor. We identified a novel, highly expressed CTLA4:CD28 gene fusion that is predicted to results in a leading to stimulatory T-cell signaling in the presence of an inhibitory signal.

  Study phs000773