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• Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

  Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

  Study EGAS00001005255

• Whole genome sequencing of mature B-cell lymphomas to identify MYC, BCL2, and BCL6 rearrangements

  Whole genome sequencing (WGS) data of 12 tumours was generated on an Illumina NovaSeq or HiSeqX instrument. For frozen samples, libraries were constructed using a PCR-free library construction method. For tumours preserved by formalin fixation and paraffin embedding (FFPE), libraries were constructed with a method that included S1 nuclease treatment. Reads were aligned to the grch37 reference with bwa-mem 0.7.17.

  Dataset EGAD50000000474

• Leukemic evolution of donor-derived cells harboring IDH2 and DNMT3A mutations after allogeneic stem cell transplantation

  An individual with acute myeloid leukemia (AML) received peripheral blood stem cell (PBSC) transplantation, but later experienced relapse. Whole-exome sequencing of bone marrow cells obtained from different stages of this patient as well as PBSC of the donor revealed that relapsed AML was not the regrowth of the original leukemic clones, but donor cell leukemia (DCL). Interestingly, some of the oncogenic mutations found in DCL were already present at a low frequency in the donor PBSC. Target deep sequencing of these genes indeed confirmed this observation, and revealed that the emergence of additional oncogenic mutations triggered leukemic evolution.

  Study JGAS000017

• IMMUcan Lung NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001558

• Comparative Sequence Analysis Between Primary and Metastatic Colorectal Cancer Lesions

  Molecular profiling for somatic mutations that predict response to anti-EGFR therapy in colorectal cancer (CRC) has become standard practice. However, abundant tissue from metastatic lesions is not always available from patients with metastatic CRC. Concerns involving genetic heterogeneity between primary and metastatic lesions have called into question the suitability of profiling primary tumors in patients with metastatic disease. Further, the identification of discordant mutations between matched primary and metastatic tumors would be of biological interest for the delineation of biomarkers of tumor progression and metastasis. To explore the degree of genetic heterogeneity between matched primary and metastatic tumors in CRC, we performed whole genome sequencing of four patient "trios" comprised of a primary colon tumor, a liver metastasis, and matched normal (non-cancerous) tissue. Somatic mutations and indels were called in each tumor and compared between primary and metastatic lesions.

  Study phs000790

• CancerDetector: Ultrasensitive and Non-Invasive Cancer Detection at the Resolution of Individual Reads using Cell-free DNA Methylation Sequencing Data

  The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed “CancerDetector”, using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation patterns of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor burden. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor DNAs. In addition, the predicted tumor burden showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1X to 10X). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.

  Study EGAS00001002728

• Cooperative Study of Sickle Cell Disease (CSSCD)

  The Cooperative Study of Sickle Cell Disease was initiated in 1977 to determine the natural history of sickle cell disease (SCD) from birth to death in order to identify those factors contributing to the morbidity and mortality of the disease. Specific objectives included: 1) to study the effect of sickle cell disease on growth and development from birth through adolescence 2) to study the conditions or events that may be related to the onset of painful crises 3) to obtain data on the nature, duration, and outcome of major complications of SCD 4) determine the nature, prevalence, and age- related incidence of organ damage due to SCD, and 5) study the role of SCD and its interaction with selected health events.Phases 2 and 3 of the study involved followup of the infant cohort. A total of 709 infants (age less than 6 months) were enrolled during Phase 1 of the Cooperative Study of Sickle Cell Disease (CSSCD), and Phases 2 and 3 of the CSSCD was designed to follow these children for an additional 10 years. The study objectives included: 1) define prospectively the natural history of sickle cell disease; 2) determine the relationships between cognitive and academic functioning and brain status as determined by MRI; 3) determine the cognitive or behavioral markers of silent infarct; 4) determine the relationship of family functioning on the Family Environment Scale (FES) to brain status, cognitive functioning, and social and demographic factors; 5) continue studies that will enhance the state of knowledge on the influence of sickle cell disease on the psychosocial adjustment of children and adolescents. Phase 2A of the study sought to examine the progression of organ damage in the heart, lung, kidney, and liver in adult cohort patients (born before 1/1/56) enrolled in phase 1 of the study between 3/79 and 5/81. A total of 620 patients from 11 centers were eligible for phase 2A.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 phs002362

• The Effects of Long-Term Heavy Metal Exposure on Transcriptome Landscape in Human Peripheral Blood Cells

  The present study investigates the impact of long-term residence in a mining area on transcriptome changes induced by heavy metal exposure in human peripheral blood mononuclear cells (PBMCs) from 65 healthy subjects selected from the general population. This study includes the same participants which were recruited in our previous investigation on heavy metal long-term environmental exposure-related gene-specific methylation changes (phs003392.v1.p1). We performed a differential expression analysis to compare the mRNA transcriptome of 31 residents from the mining region (MRR) - individuals living in the Kapan mining area with reported environmental exposures to heavy metals - with that of 34 residents from non-mining regions (NMR) - individuals residing at a considerable distance from mining locations. We also evaluated the potential association of gene expression profiles with the blood metallome, including levels of Ca, Mg, Co, Fe, Mn, Cu, Mo, Se, Zn, As, Sb, Tl, Be, V, Ni. Poly-A selected strand-specific mRNA library was prepared with Illumina Stranded mRNA Prep kit. The sequencing was performed on the Illumina NovaSeq-6000 platform with 38.5 million single-end 100 bp reads on average generated per sample. Quality checking of the sequencing data was performed using Illumina Basespace reports and the program FastQC (V0.10.1). Reads were aligned against the Human Genome Hg38 using STAR (version 2.7.1a). According to our findings, long-term residence in a mining area is correlated with alterations in the blood transcriptome, with responses varying by sex. Pathway analysis revealed upregulation of immune response related pathways, and downregulation of translation and ribosome biogenesis in the PBMCs of the MRR. Pathways related to metal ion transmembrane transport, epigenetic modifications (histone deacetylases (HDACs) and DNA methylation) were upregulated in males, while in females mostly transcripts involved in inflammation and cytokine mediated signaling were upregulated. Additionally, among the dysregulated pathways, the TNF-α signaling via NF-κB showed opposite changes in females and males.

  Study phs003657

• 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

• Whole genome sequencing of Osteosarcoma clonal evolution

  Multiple large-scale genomic profiling efforts have been undertaken in osteosarcoma to define the genomic drivers of tumorigenesis, therapeutic response, and disease recurrence. The spatial and temporal intratumor heterogeneity could also play a role in promoting tumor growth and treatment resistance. Here, we conducted longitudinal whole-genome sequencing of 37 tumor samples from eight patients with osteosarcoma that relapsed or became refractory to initial therapy. We found that the chemoresistant population in recurrent osteosarcoma is subclonal at diagnosis, emerges at the time of primary resection due to selective pressure from neoadjuvant chemotherapy, and is characterized by unique oncogenic amplifications.

  Dataset EGAD00001011285

• Mesothelioma Genomics Study - WGS tumour/normal pairs

  Malignant mesothelioma (MM) is an incurable and aggressive tumour that occurs principally in the pleura as a consequence of inhaling asbestos fibres. There are >15,000 cases per annum worldwide, the incidence is increasing and Australia has one of the world's highest incidence rates. Surgery, chemotherapy and radiotherapy (or their combinations) all feature in the clinical management but do not impact significantly on overall survival. This study uses whole genome sequencing (WGS) with the aim of identifying mesothelioma-related genomic alterations and potentially identifying novel treatment strategies.

  Study EGAS00001002299

• Rna-Seq Leiomyosarcoma subtypes

  Leiomyosarcomas (LMS) are genetically heterogeneous tumors differentiating along smooth muscle lines. Currently, LMS treatment is not informed by molecular subtyping and is associated with highly variable survival. While disease site continues to dictate clinical management, the contribution of genetic factors to LMS subtype, origins, and timing are unknown. Here we analyzed 70 genomes and 130 transcriptomes of LMS, including multiple tumor regions and paired metastases. Molecular profiling highlighted the extremely early origins of LMS. Three specific subtypes of LMS develop from distinct lineages of smooth muscle cells. Of these, dedifferentiated LMS with high immune infiltration and tumors primarily of gynaecological origin acquired the highest burden of genomic mutation and are associated with worse survival. Homologous recombination defects lead to genome-wide mutational signatures, and a corresponding sensitivity to PARP and other DNA damage response inhibitors, suggesting a novel therapeutic strategy for LMS. Finally, by phylogenetic reconstruction, we present evidence that clones seeding lethal metastases arise decades prior to LMS diagnosis.

  Study EGAS00001004783

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• Center for Common Disease Genomics (CCDG) - Cardiovascular: Cleveland Clinic Cohort

  The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study contains variant calls derived from the whole genome sequence data of an early-onset coronary artery disease case-control cohort collected by the Cleveland Clinic. Case status was assigned based on the presence of myocardial infarction, coronary artery stenosis greater than 70% in at least one coronary artery, and/or revascularization (coronary angioplasty with or without stent placement or coronary artery bypass grafting) at an early age. For these samples, "early age" is defined as men 60 years of age or younger and women 70 years of age or younger.

  Study phs001871

• Correlates of Human Nerve Repair

  This is a longitudinal prospective cohort study in patients with carpal tunnel syndrome undergoing decompression surgery. Phenotypic data and skin biopsies were collected before and 6 months after surgery to determine molecular and cellular correlates associated with neural regeneration and neuropathic pain. RNA sequencing was performed in the skin samples and differential gene expression was determined post compared to pre surgery. The molecular changes identified in skin were correlated with the clinical phenotype representing neural regeneration.

  Study phs001796

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Mediators of Atherosclerosis in South Asians Living in America Study (MASALA)

  Cohort Description The Mediators of Atherosclerosis in South Asians Living in America (MASALA) study is a prospective cohort of South Asians that aims to identify risk factors for heart disease in a large, growing Asian American subgroup. MASALA enrolled 906 South Asians in 2010-2013 and then added a new wave of 258 South Asian participants from 2017-2018, for a full cohort size of 1,164. Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 431 MASALA participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 313 MASALA participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 248 MASALA participants in C4R. Derived data includes 43 variables for up to 528 MASALA participants in C4R. Phenotype data includes 113 variables for up to 429 MASALA participants in C4R.

  Study phs002980

• Genetic sequencing of MODY patients.

  Maturity-onset Diabetes of the young (MODY) is an early-onset, autosomal dominant form of non-insulin dependent diabetes. Genetic diagnosis of MODY can transform patient management. Earlier data on the genetic predisposition to MODY have come primarily from familial studies in populations of European origin. Using next generation sequencing, we carried out a comprehensive genomic analysis of 289 individuals from India that included 152 clinically diagnosed MODY cases to identify variants in known MODY genes. Our findings report that HNF1A and ABCC8 are among the most frequently mutated MODY genes in south India.

  Study EGAS00001001699

• Analysis of translatome, truncating mutations, lncRNA, circRNA and microproteins of 80 human DCM cases and controls

  The regulation of gene expression in healthy and diseased human tissues is incompletely understood and has primarily been studied on the transcriptional level. Here, we quantify the impact of translation on gene expression and annotate novel translational events in 80 human hearts. These include 65 tissues from patients with dilated cardiomyopathy (DCM) - the most common cause of heart transplantation – and 15 unaffected controls. We show that translational regulation modulates disease-associated molecular processes. Further, we evaluate ribosome dynamics at protein truncating variants revealing incomplete termination of translation at titin-truncating variants (TTNtv) that commonly cause DCM. Finally, we identify dozens of unknown microproteins translated from lncRNAs and circRNAs and link these to mitochondrial processes. Several microproteins are expressed from lncRNAs with previously demonstrated function, suggesting a dual coding and noncoding role. This resource will stimulate novel functional investigations into cardiac biology in health and disease and may serve as a blueprint for characterizing the translational landscape of other human tissues.

  Study EGAS00001003263

• GOSH_Childhood_Leukemia_Behjati_WellcomeCore_RNA

  Paediatric single-cell archival project This project is taking sequential samples of children with B-cell acute lymphoblastic leukaemia (B-ALL) treated at Great Ormond Street Hospital (GOSH) between 2011 and the present day. Patients selected, are those that have done badly (e.g. had to escalate treatment, relapsed or died) despite having apparently ""good"" or ""intermediate"" risk cytogenetics, and often also had immunotherapy (e.g., the bi-specific T-cell engager blinatumomab) because of this. Using samples from key treatment-points, we hope to better characterise their disease and treatment response, to re-define understandings of risk for patients who did unexpectedly poorly. Additionally, we hope to define the disease/immunological factors that determine response to increasingly used immunotherapies within the field of paediatric B-ALL. Each of the samples will be viably frozen bone marrow-derived mononuclear cells. They will come in Eppendorf's, frozen and de-anonymised, from GOSH. We plan to primarily do single cell analysis (GEX, BCR +/-TCR), and then tumour-only WGS and bulk-RNA expression on left-over

  Study EGAS00001007616

• iNHL WXS Data Commitee

  The iNHL WXS Data Commitee is responsible for managing access to datasets submitted to the European Genome-phenome Archive (EGA). Our committee ensures that access requests are evaluated in compliance with ethical guidelines, regulatory requirements, and the conditions specified by data submitters. Researchers requesting access to these datasets must provide a clear and valid scientific purpose, demonstrate affiliation with a recognized institution, and agree to the terms of use outlined in the Data Access Agreement. The iNHL WXS Data Commitee works to uphold data privacy and security while facilitating responsible data sharing to advance scientific discovery. For further information on our policies or the application process, please contact Hauke Busch (hauke.busch@uni-luebeck.de).

  Dac EGAC50000000488

• Neo-RT sWGS

  Paired plasma cell-free DNA (cfDNA) samples were collected from 11 breast cancer patients before and after radiotherapy. Sequencing libraries were prepared using the Agilent SureSelect XT HS2 kit and sequenced on the Illumina NovaSeq 6000 platform. Neo-RT (NCT03818100) is a non-randomised, single-arm feasibility study evaluating neoadjuvant radiotherapy combined with endocrine therapy in women with ER-positive, HER2-negative breast cancer. Eligible patients had grade 1 or 2 disease (grade 3 permitted if chemotherapy was contraindicated) and a palpable tumour size ≥20 mm, for whom radiotherapy was intended to facilitate breast-conserving surgery.

  Dataset EGAD50000002238

• Risk Factors for Asymptomatic Diverticulosis

  Data for this analysis came from a prospective study of colonic diverticulosis at the University of North Carolina Hospital in Chapel Hill, North Carolina (NIH R01DK094738). This is a case-control genetic and transcriptomic study to identify the genetic and cellular determinants underlying colonic diverticulosis and the relationship with other gastrointestinal disorders. The study inclusion and exclusion are described below. DNA and RNA sequencing were performed on colonic tissue from 404 patients with (N=172) and without (N=232) diverticulosis. We assessed variation in the transcriptome associated with diverticulosis and integrated this variation with human intestine single-cell RNA-seq data. We integrated our expression quantitative trait loci with GWAS using Mendelian Randomization. A polygenic risk score analysis examined associations between severity of diverticulosis and other gastrointestinal disorders. We identified 38 genes with differential expression and 17 genes with varied transcript usage linked to diverticulosis. Our results suggest tissue remodeling as a primary mechanism for diverticula formation. The presence of diverticulosis was linked to stromal and epithelial cells in the colon including endothelial cells, myofibroblasts, fibroblasts, goblet, tuft, enterocytes, neurons, and glia. MR highlighted five genes including CCN3, CRISPLD2, ENTPD7, PHGR1, and TNFSF13. In diverticulosis cases, ENTPD7 upregulation was confirmed. A greater burden of diverticula was positively correlated with genetic predisposition to diverticulitis. The data related to the study including total RNA-Seq, SNP array and imputed genotypes will be available through dbGaP.

  Study phs003556