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• Cancer-Associated Mutations in Endometriosis without Cancer

  Endometriosis, defined as the presence of ectopic endometrial stroma and epithelium, affects approximately 10% of reproductive-age women and can cause pelvic pain and infertility. Endometriotic lesions are considered to be benign inflammatory lesions but have cancerlike features such as local invasion and resistance to apoptosis

  Study EGAS00001003576

• Whole exome sequencing of 76 individuals with familial atrial fibrillation

  We investigated genetic background of familial and early onset atrial fibrillation (AF) with the aim of identify genes involved in atrial fibrillation pathology and are highly predisposing risk factors. We performed whole exome sequencing on 24 families where three or more family members suffered from AF.

  Study EGAS00001003207

• Next Generation Sequencing Characterization of Hematopoietic Stem and Progenitors Cells in Human Systemic Lupus Eryhtematosus

  This dataset contains RNA-sequencing of Bone marrow-derived CD34+ cells from Healthy Controls (n=2) and SLE patients (n=8). SLE patients are divided into two categories based on severity: patients with moderate/mild disease (n=3) and patients with severe disease (n=5). Libraries were generated using the Illumina TruSeq Sample Preparation kit v2. Single-end 75-bp mRNA sequencing was performed on Illumina NextSeq 500. The raw fastq files are uploaded.

  Dataset EGAD00001005052

• Next Generation Sequencing Characterization of Hematopoietic Stem and Progenitors Cells in Human Systemic Lupus Eryhtematosus (2)

  This dataset contains RNA-sequencing of Bone marrow-derived CD34+ cells from Healthy Controls (n=2) and SLE patients (n=10). SLE patients are divided into two categories based on severity: patients with moderate/mild disease (n=4) and patients with severe disease (n=6). Libraries were generated using the Illumina TruSeq Sample Preparation kit v2. Single-end 75-bp mRNA sequencing was performed on Illumina NextSeq 500. The raw fastq files are uploaded.

  Dataset EGAD00001009744

• Recalibrated alignment files of Saudi Thyroid Cancer

  The dataset consists of samples from papillary thyroid cancer patients. A total of 292 DNA samples from blood/normal and cancer tissue are subjected to whole exome sequencing using Illumina. The fastq files generated were aligned with reference genome ‘hg19’, duplicates were marked, realignment around indels and quality recalibration were performed to produce good quality variants. The recalibrated “.bam” files are included with this dataset.​

  Dataset EGAD00001003950

• GEnetics of Nephropathy - an International Effort (GENIE) GWAS of Diabetic Nephropathy in the UK GoKinD and All-Ireland Cohorts

  Diabetic kidney disease, or diabetic nephropathy (DN), is one of the leading causes of end-stage renal disease in the United States and worldwide. DN is a common complication of long-standing type 1 and type 2 diabetes. The clinical course is characterized by development of proteinuria and gradual loss of kidney function. Although existing treatments that decrease proteinuria have been shown to moderately abate progression of diabetic kidney disease, many affected patients, who do not die from cardiovascular disease, go on to develop terminal renal failure, necessitating costly renal replacement therapies, such as dialysis and renal transplantation. Type 1 diabetes (T1D) can have its onset in childhood and affected individuals often develop end-stage renal disease in early adulthood, leading to further loss of quality of life. The genetic basis of the disease is not well understood. The GENIE (GEnetics of Nephropathy an International Effort) consortium was initiated to perform the most comprehensive and well powered DN susceptibility genome wide association study (GWAS) analysis to date, using the largest collection of type 1 diabetics with and without kidney disease across four study cohorts. The UK-ROI samples were genotyped as part of this project. UK-ROI Sample Description The UK-ROI collection consists of samples derived from the Republic of Ireland (Dr. Catherine Godson, PI, at University College, Dublin, Ireland) and the United Kingdom (Warren 3 and Genetics of Kidneys in Diabetes UK, UK GoKinD, Dr. Alexander P. Maxwell, PI, at Queen's University of Belfast, UK). All study subjects met the inclusion criteria: white individuals with T1D, diagnosed before 31 years of age, whose parents and grandparents were born in the British Isles.

  Study phs000389

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  RNA sequencing is widely used to study gene abundance patterns, but less frequently to assess structural alterations such as fusion transcripts. In this study, we assess the performance of messenger RNA (mRNA) capture sequencing to identify fusion transcripts in formalin-fixed paraffin-embedded (FFPE) tissue of different types of sarcoma, followed by orthogonal confirmation using RT-qPCR. To validate our workflow, we used the TruSight RNA Pan-Cancer Panel to analyze a first cohort of 6 positive control tumors for which the diagnostic workup demonstrated the presence of a specific chromosomal rearrangement. Fusion transcript calling by FusionCatcher confirmed all known aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole transcriptome TruSeq RNA Exome sequencing was applied to a second cohort of 17 patients, diagnosed with fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS), for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. Remarkably, for 6 out of 17 patients, mRNA capture sequencing readily detected a pathognomonic fusion transcript, i.e. PAX3-FOXO1 in 2 ARMS patients, and EWSR1-FLI1, EWSR1-ERG or EWSR1-NFATC2 in 4 URCS patients. These data show that RNA capture sequencing may enhance the detection rate of pathognomonic fusion genes in sarcoma. For the 11 patients with no known pathognomonic fusion transcript, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2 and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in two patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53 and UBE2F-ALS2). Our results provide new insights into the underlying genetic causes of these malignancies.

  Study EGAS00001005202

• Lung cancer organoids

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004013

• Lung cancer organoids addition

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term culture conditions of human airway epithelial organoids that contain all major cell populations and allow personalized human disease modelling. We collected macroscopically inconspicuous lung tissue from non-small-cell lung cancer (NSCLC) patients undergoing medically indicated surgery and isolated epithelial cells to engineer 3D organoids. We exploit the potential to derive sub-clones from AOs to demonstrate the feasibility of CRISPR gene editing. Finally, we show that AOs readily allow modelling of viral infections such as RSV and for the first time demonstrate the possibility to study neutrophil-epithelium interaction in an organoid model. Taken together, we anticipate that human AOs will find broad applications in the study of adult human airway epithelium in health and disease.

  Dataset EGAD00001004943

• RNA-Seq dataset of Targeting the dark proteome to expand the lineage-retained antigen landscape in neuroblastoma

  This dataset contains bulk RNA-sequencing data generated to enable custom transcriptome assembly and to provide expression context for matched ribosome profiling in the discovery of lineage-retained neuroblastoma tumor antigens. RNA was sequenced from 183 neuroblastoma samples comprising cell lines, patient-derived tumor organoids, and primary patient tumors spanning the adrenergic (ADRN) and mesenchymal (MES) lineage states, with 101 samples prepared as rRNA-depleted (total RNA) libraries and 82 samples prepared as poly(A)-selected libraries. Libraries were sequenced paired-end (2x150 bp) on the Illumina NovaSeq 6000 platform. Raw data are provided as paired-end fastq.gz files.

  Dataset EGAD00001016124

• Ameloblastoma Cell Line Resource

  Ameloblastoma (AB) is an odontogenic tumor that is locally destructive to the jaw bone. Treatment entails surgical resection, but AB often recurs locally. Recent driver mutations have been identified in the MAPK and Hedgehog pathways. However, translation to molecularly-targeted therapies has been hampered by the lack of AB cell line models. The goal of our study has been to create a new AB cell line resource that reflects the spectrum of AB driver mutations. We created 6 new AB cell lines, and by targeted exome sequencing, defined their driver mutations. We showed the utility of these cell lines in preclinical studies of oncogene dependence and drug sensitivity (which includes whole transcriptome assays).

  Study phs002753

• Genome-wide integrative analysis of pediatric pancreatoblastoma

  Pancreatoblastoma is the most common pancreatic malignancy of young children, but its molecular pathogenesis remains poorly understood. To understand the molecular pathogenesis of pancreatoblastoma, we comprehensively analysed the whole exome sequencing, RNA sequencing, SNP array, and methylation array data of pancreatoblastoma.

  Study JGAS000088

• RNA-seq of granulosa cells from 8 IVF patients in two age groups

  This dataset contains raw sequencing data of mRNA from granulosa cell samples from 8 human patients undergoing in vitro fertilization. All patients were normal responders referred for male infertility and were grouped into two age groups (younger than 31 or older than 38 years old). Each sample contains all granulosa cells collected from one patient on one collection date. Raw sequencing fastq files are available in this dataset, count tables are available in ArrayExpress (E-MTAB-13496).

  Dataset EGAD50000001210

• Investigating Delayed-Onset Drug Hypersensitivity Reactions Prospectively

  Delayed-type drug hypersensitivity reactions (dtDHR) are significant causes of morbidity and mortality, but the origin, phenotype and function of pathogenic T cells across the spectrum of severity are unknown. Research has been hampered by several barriers. We leveraged recent technical advancements to study skin-resident memory T cells (TRM) versus recruited T cell subsets in the pathogenesis of severe systemic forms of disease, Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN) and drug reaction with eosinophilia and systemic symptoms (DRESS), and skin-limited disease, morbilliform drug eruption (MDE). As part of the overarching study, we used single cell RNA sequencing (scRNA-seq) with CITE sequencing and TCR sequencing on prospectively collected skin and blood samples from patients with SJS/TEN and MDE patients. We compared this to healthy controls obtained from discarded skin from surgeries and discarded blood collars from a blood donation center. These data are included here in dbGaP database. The overarching study also performed bulk transcriptional profiling and microscopic analysis of clinical skin samples, as well as a mouse model of MDE (PMID: 39042477). Together, the data supported clonal expansion and recruitment of cytotoxic CD8+ T cells (identified using the mean normalized expression of NKG7, GNLY, GZMA, GZMB, and PRF1) from circulation into skin, along with both expanded and non-expanded cytotoxic CD8+ skin TRM in SJS/TEN whereas MDE displayed a cytotoxic T cell profile without expansion or recruitment of cytotoxic CD8+ T cells from circulation implicating TRM as the potential cause of disease. Concurrently, MDE displayed a pro-Treg signature, highlighted by CCR8 and TNFRSF4 (OX40), which promotes Treg survival compared to SJS/TEN.

  Study phs003344

• Molecular features of adenomas predicting metachronous colorectal cancer: a nested-case control study

  "Background & Aims: Current morphological features defining advanced adenomas (size ≥10 mm, high grade dysplasia or >25% villous component) cannot optimally distinguish individuals at high-risk or low-risk of metachronous colorectal cancer (me-CRC), which may result in suboptimal surveillance. Certain DNA copy number alterations are associated with adenoma-to-carcinoma progression (cancer-associated events; CAEs). We aimed to evaluate whether CAEs can better predict an individual’s risk of me-CRC than the morphological advanced adenoma features. Methods: In this nested case-control study, 529 individuals with a single adenoma at their first colonoscopy were selected from a Norwegian adenoma cohort. DNA copy number profiles were determined, by means of low-coverage whole genome sequencing. We assessed the prevalence of CAEs in advanced and non-advanced adenomas and its association with me-CRC. For the latter, cases (with CRC) were matched to controls (without CRC), with the same follow-up period as cases, as well as age and sex. Subsequently, odds ratios (OR) for the association of the presence of an advanced adenoma or a molecularly-defined high-risk adenoma with me-CRC were calculated. Results: Molecular high-risk features were observed in 85/267 (32%) of advanced adenomas and in 27/262 (10%) of non-advanced adenomas. Me-CRC was more strongly associated with advanced adenomas (OR 3.58; 95% CI 2.27-5.72) than with molecular high-risk adenomas (OR 1.90; 95% CI 1.14–3.16). After adjusting for other variables, only advanced adenoma remained significantly associated with me-CRC (OR 3.39; 95% CI 2.10–5.55). Conclusion: Molecularly-defined high-risk adenomas were associated with me-CRC, but the association of advanced adenoma with me-CRC was stronger. " Project goal: Evaluate the value of DNA copy numbers alterations detected in a baseline adenoma, in the prediction of risk of metachronous CRC

  Study EGAS00001007039

• Adenoma to Carcinoma transition in Colorectal Cancer

  Although colorectal carcinoma development is well accepted as a step-wise and sequential process, it is commonly investigated using non-sequential adenoma and carcinoma samples. Here we compared molecular pathologies of the earliest carcinoma stages with those in their adenomatous precursors to unravel common and divergent genetic traits between matched neoplasms with a shared evolutionary history but different contemporary biology.

  Study EGAS00001003468

• ARRA - NHLBI Lung Cohorts Sequencing Project: Genetic modifiers of

  The major goal of this project is to apply second generation resequencing technology to identify disease causing variants influencing pediatric and adult lung diseases in a collection of two longitudinal population cohorts of cystic fibrosis patients that have been well characterized for a comprehensive set of clinical traits. In Phase I, exome sequencing was performed on 43 cystic fibrosis patients with early Pa infection and 48 cystic fibrosis patients with late Pa infection to identify variants influencing the time to onset of Pa infection. In Phase II, additional exomes were added to the study, to reach a total of 91 individuals with early Pa infection and 96 with late Pa infection. The majority of the 340 subjects of Phase II do not have a Pa infection phenotype, but instead have a pulmonary function phenotype (121 severe vs. 124 mild impairment) as determined by the survival corrected Kulich FEV percentile of Corey et al. A small minority have intermediate phenotypes and/or show severe decline in lung function during childhood.

  Study phs000254

• Blood DNA Methylation in Post-Acute Sequelae of COVID-19 (PASC): a Prospective Cohort Study

  Background: DNA methylation integrates environmental signals with transcriptional programs. COVID-19 infection induces changes in the host methylome. While post-acute sequelae of COVID-19 (PASC) is a long-term complication of acute illness, its association with DNA methylation is unknown. No universal blood marker of PASC, superseding single organ dysfunctions, has yet been identified. Methods: In this single center prospective cohort study, PASC, post-COVID without PASC, and healthy participants were enrolled to investigate their symptoms association with peripheral blood DNA methylation data generated with state-of-the-art whole genome sequencing (WGS). PASC-induced quality-of-life deterioration was scored with a validated instrument, SF-36. Analyses were conducted to identify potential functional roles of differentially methylated loci, and machine learning algorithms were used to resolve PASC severity. Findings: 103 patients with PASC (22.3% male, 77.7% female), 15 patients with previous COVID-19 infection but no PASC (40.0% male, 60.0% female), and 27 healthy volunteers (48.1% male, 51.9% female) were enrolled. Whole genome methylation sequencing revealed 39 differentially methylated regions (DMRs) specific to PASC, each harboring an average of 15 consecutive positions, that differentiate patients with PASC from the two control groups. Motif analyses of PASC-regulated DMRs identify binding domains for transcription factors regulating circadian rhythm and others. Some DMRs annotated to protein coding genes were associated with changes of RNA expression. Machine learning support vector algorithm and random forest hierarchical clustering reveal 28 unique differentially methylated positions (DMPs) in the genome discriminating patients with better and worse quality of life.

  Study phs003658

• Accurate mutation detection in leukemia by re-sequencing a cancer gene set

  With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using the Roche/454 technology coupled with Nimblegen sequence capture. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely BWA-SW and SSAHA2, coupled with the variant calling algorithm Atlas-SNP2 yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations.

  Study EGAS00001000268

• BAM files ChIP-Seq

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001669

• ChiLDReN/BA: Genetic Studies of Biliary Atresia in the Childhood Liver Disease Research Network

  Biliary atresia (BA) is a progressive necroinflammatory process initially involving the extra-hepatic biliary tree. Little is known about the factors that cause BA or the factors that influence disease progression. A variety of genetic, autoimmune, and environmental influences have been hypothesized to be important. Most studies to date have focused on the neonate and young child with BA, yet the older surviving child with BA can provide important information about genetics as well as natural history.The Childhood Liver Disease Research Network (ChiLDReN) conducts two longitudinal and observational studies that include BA patients: Biliary Atresia Study in Infants and Children (BASIC) and A Prospective Database of Infants with Cholestasis (PROBE). Using samples from participants in these two protocols, we have formed the largest known data set of biliary atresia patients in the world. ChiLDReN is performing a series of genomic analyses, with subsequent analyses being released as subsequent versions of this registration, phs003356. Version 1 concerns PKD1L1.About the PKD1L1 Analysis (phs003356.v1): While multiple factors have been implicated in the perinatal biliary injuries that characterize BA, a definitive etiology has not yet been established. This study is part of a larger project to characterize the largest cohort of pediatric BA patients through whole-exome sequencing (WES). In this analysis, we examine the WES of those with various laterality defects to determine whether genetic factors could be identified to explicate the etiopathogenesis of BA in biliary atresia splenic malformation (BASM) syndrome. We specifically explored variations in the PKD1L1 gene, which recently has been identified in mouse models as playing a role in laterality.

  Study phs003356

• Targeted analysis of cell-free circulating tumor DNA is suitable for early relapse and actionable target detection in patients with neuroblastoma

  Study EGAS00001006027

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• Genome-Wide Association Analysis of Biomarkers in the InCHIANTI and BLSA

  Version 1 The aim of this study was to identify gene(s) associated with serum iron concentrations. This dataset contains the results from a meta-analysis of 1919 subjects from the InCHIANTI and Baltimore Longitudinal Study of Aging (BLSA). Both studies are population based prospective studies that evaluate the contributors of normal aging. Version 2 We performed genome wide analysis of 93 circulating biomarkers in the InCHIANTI study of 1210 individuals, after imputation from the 1000 genomes project.

  Study phs000215