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• Transrenal DNA Analysis

  Urinary cell-free DNA (ucfDNA) is an emerging marker in liquid biopsy. However, the characteristics of transrenal DNA and urinary-tract DNA are not fully understood. Therefore, we investigated the fragmentomic features and demonstrated the potential clinical utilities of ucfDNA in the current study.

  Study EGAS50000000766

• End structure of DNA in plasma: detection, characterizationand diagnostic applications

  The physical properties of cell-free DNA fragments in plasma, such as fragment sizes and ends, have attracted much recent interest, leading to the emerging field of fragmentomics. This study attempted to further characterize the end structure of plasma DNA.

  Study EGAS00001004080

• Frequent mutation of the FOXA1 untranslated region in prostate cancer

  We sequenced the coding and untranslated regions of 72 prostate cancer driver genes in 712 plasma cell free DNA samples from 428 men with metastatic prostate cancer, in an effort to understand the role of untranslated region mutations in late stage prostate cancer.

  Study EGAS00001003113

• shallow WGS of cell free DNA

  12.5 ng of cfDNA was used as input for shallow whole-genome sequencing (sWGS), aiming for a coverage of x0.2-0.4-fold. Library preparation was performed using the TruSeq Nano DNA High Throughput Library Prep Kit (Illumina, San Diego, CA, USA) on an automated Hamilton STAR liquid handling system (Hamilton, Germany GmbH, Robotics, Gräfeling, Germany) with dual indexing, and sequencing was performed on the NextSeq500/550 platform (Illumina). The fraction of tumor-derived DNA in cell-free DNA was estimated using the R package ichorCNA.

  Dataset EGAD00001009796

• Low-coverage whole genome methylation sequencing of cell-free DNA from healthy volunteers and allograft transplant recipients

  Low-coverage whole genome methylation sequencing of cell-free DNA (cfDNA) from healthy volunteers (n=2) and allograft transplant recipients (n=11). The cfDNA was extracted from urine and plasma and sequenced using both a single- and double-strand library preparation method (n=15 and n=18).

  Dataset EGAD00001010937

• De novo mutations in cell-free foetal DNA (cffDNA)

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000596

• Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA

  This dataset contains a total of 10 families and 51 samples presented in 'Non-invasive prenatal diagnosis by genome-wide haplotyping of cell-free plasma DNA' study, in which 9 of them are cfDNA samples and the rest of samples are gDNA samples. All the samples are targeted sequencing data with a custom 45Mb capture library . Raw pair-end fastq files for each sample is available.

  Dataset EGAD00001004989

• Copy number profiling of circulating cell-free DNA from high grade serous ovarian cancer patients

  Study EGAS00001004670

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• Test Study for EGA using data from 1000 Genomes Project - Phase 3

  The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

  Study EGAS00001005042

• Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome

  Background The methylation pattern of cfDNA, isolated from liquid biopsies, is gaining substantial interest for diagnosis and monitoring of diseases. We have evaluated the impact of type of blood collection tube and time delay between blood draw and plasma preparation on bisulfite-based cfDNA methylation profiling. Methods 15 tubes of blood were drawn from three healthy volunteer subjects (BD Vacutainer K2E EDTA spray tubes, Streck Cell-Free DNA BCT tubes, PAXgene Blood ccfDNA tubes, Roche Cell-Free DNA Collection tubes and Biomatrica LBgard blood tubes in triplicate). Samples were either immediately processed or stored at room temperature for 24 or 72 hours before plasma preparation. DNA fragment size was evaluated by capillary electrophoresis. Reduced representation bisulfite sequencing was performed on the cell-free DNA isolated from these plasma samples. We evaluated the impact of blood tube and time delay on several quality control metrics. Results All preservation tubes performed similar on the quality metrics that were evaluated. Furthermore, a considerable increase in cfDNA concentration and the fraction of it derived from NK cells was observed after a 72-hour time delay in EDTA tubes. Conclusion The methylation pattern of cfDNA is robust and reproducible in between the different preservation tubes. EDTA tubes processed as soon as possible, preferably within 24 hours, are the most cost effective. If immediate processing is not possible, preservation tubes are valid alternatives.

  Study EGAS00001004271

• Differential Presence of Exons in Cell-Free DNA Reveals Different Patterns in Colorectal Cancer Between Metastatic and Non-Metastatic Patients

  Dac EGAC00001000749

• The cell free DNA methylome of primary and metastatic prostate tumors

  Study EGAS00001005522

• Immune microenvironment and lineage tracing help deciphering Rosette-forming GlioNeuronal Tumors: a multi-omic analysis of 9 cases

  Rosette-forming GlioNeuronal Tumor (RGNT) is a rare central nervous system neoplasm containing two components, glial and neuronal. The delineation of histological diagnosis of RGNT from similar low-grade tumors such as pilocytic astrocytoma (PA) and ganglioglioma (GG) may be challenging. We performed here a comprehensive molecular analysis of a cohort of tumors with same histology features to identify molecular characteristics of RGNT. A cohort of 9 rosette-forming tumors histologically-diagnosed were analyzed at molecular level using multimodal approaches as Whole Exome Sequencing (WES), RNAseq and methylome. In our cohort, 3 tumors were plotted within the Methylation Class-RGNT (MC-RGNT) characterized by FGFR1 mutation associated with PIK3CA or NF1 mutations. Transcriptome analysis was performed in 7 cases. RNAseq identified a “Hot” and a “Cold” transcriptomic group; the latter includes the 3 MC-RGNT and 1 MC-Pilocytic Astrocytoma and exhibited a “Cold” immune tumor microenvironment in comparison with the “Hot” group. The distinct immune cell content of both groups was confirmed by quantitative immunostainings. Get Set Enrichment Analysis showed that the “Cold” group had upregulated NOTCH pathway and mainly oligodendrocyte precursor cell and neuronal phenotypes while the “Hot” group exhibited predominantly astrocytic and neural stem cell phenotypes. In silico deconvolution identified the cerebellar granule cell lineage as a putative origin and as the cell context to understand the effects of genetic alterations and NOTCH signaling. Histological diagnosis of rosette-forming tumors encompasses heterogeneous tumor entities. Our study identified distinct tumor cell contexts and microenvironments as key features to better understand and manage these neoplasms.

  Study EGAS00001006502

• Data access committee for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer

  Dac EGAC00001001435

• The data access committee for Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  Dac EGAC50000000588

• The data access committee for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  Dac EGAC00001003253

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Study EGAS00001004975

• WGS & RNAseq of paired tumor-normal patients presenting a BRCA2 alteration

  Raw data FASTQ files of RNAseq (Stranded mRNA prep Ligation-Illumina on NovaSeq 6000, 100bp paired-end) & WGS (PCR Free Roche KAPA Hyper Prep Library on Illumina Novaseq 6000, 150bp paired-end) for 40 samples corresponding to the matched tumor/normal of 10 patients. Raw data FASTQ files of WGS (PCR Free Roche KAPA Hyper Prep Library on Illumina Novaseq 6000, 150bp paired-end) of the tumor of two additional patients.

  Dataset EGAD50000000871

• Stratified Medicine Paediatrics (SMPaeds): molecular profiling of relapsed paediatric cancer

  We profiled a large heterogenous cohort of matched diagnostic-relapse tumour tissue and plasma-derived cell free DNA (cfDNA) from patients with relapsed and progressive solid tumours of childhood. Tumour DNA and cfDNA were analysed by targeted panel sequencing and low coverage whole genome sequencing.

  Study EGAS50000000549

• Metagenomic sequencing of fecal samples from celiac disease patients and controls

  150 nt paired-end metagenomic shotgun sequencing (Illumina HiSeq 2000) of fecal samples from 130 (mostly treated, i.e. adhering to gluten-free diet) celiac disease patients and 106 controls from the CeDNN cohort from the University Medical Center Groningen, The Netherlands. For six celiac disease patients, data from two timepoints (before and during gluten-free diet) are included, resulting in a total of 242 samples. The dataset includes 2 encrypted fastq files per sample (.fq.gz.c4gh) en sample phenotypes (.txt.c4gh).

  Dataset EGAD50000001397

• Targeted gene expression analysis on FFPE specimen from NSCLC patients

  This study measured the expression of a panel of over 300 cancer immunotherapy-relavant genes in tumors after neoadjuvant chemoimmunotherapy. It was performed on RNA from FFPE tumor tissue. Differential gene expression analysis was performed between patients achieving or not achieving an event-free survival of 12 months.

  Study EGAS50000001140

• cell-free Nucleosome ChIP-seq

  Dataset includes cell-free ChIP-seq data of 268 samples (from 61 self-declared healthy donors, four patients with acute myocardial infarction, 29 patients suffering from autoimmune, metabolic, or viral liver diseases and 56 metastatic colorectal carcinoma (CRC) patients). DNA libraries preparation is documented in the methods section. Libraries were paired end sequenced by Illumina NextSeq 500 and aligned to the human genome (hg19) using bowtie2 (2.3.4.3) with ‘no-mixed’ and ‘no-discordant’ flags. This dataset includes fastq and BAM files of all samples.

  Dataset EGAD00001006811

• FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

  28 patients. Cell-free DNA and leukocyte DNA, both from before any neoadjuvant treatment. Tumor FFPE tissue (plus metastasic tissue for some patients) from after any neoadjuvant treatment. Some cfDNA from follow-up time points (e.g. after neodj. treatment or in the clinical course). IDT xgen Pan-Cancer panel for hybridisation capture. Illumina TruSeq library prep for cfDNA and leukocyte DNA, Illumina DNA Prep for FFPE DNA. n=150 libraries in total.

  Dataset EGAD00001010081

• The dataset for Detecting Liver Cancer Using Cell-Free DNA Fragmentomes

  The dataset for Detecting Liver Cancer Using Cell-Free DNA Fragmentomes includes 444 BAM files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010931

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

  Study EGAS00001006027

• Acute Respiratory Distress Network (ARDSNet) Studies 10 and 12 Statins for Acutely Injured Lungs from Sepsis (SAILS) (ARDSNet-SAILS-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-SAILS include Plasma, DNA, and Urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The SAILS trial was intended to assess the efficacy and safety of oral rosuvastatin in participants with sepsis-induced Acute Lung Injury (ALI) and test the hypothesis that rosuvastatin therapy would improve the clinical outcomes of critically ill participants with sepsis-associated acute respiratory distress syndrome (ARDS). Background In ARDS, inflammation in the lungs and other organs can cause life-threatening organ failure. Inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A reductase (statins) can modulate inflammatory responses. Previous observational studies suggested that statins improved clinical outcomes in participants with sepsis. Participants There were 745 participants. Design Participants were randomly assigned in permuted blocks to receive either enteral rosuvastatin or placebo. A 40 mg loading dose of the study drug was administered within four hours after randomization. Subsequently, maintenance doses of 20 mg were administered daily until the third day after discharge from the intensive care unit, study day 28, hospital discharge, or death, whichever came first. The primary outcome measure was mortality before hospital discharge home or until study day 60 if the participant was still in a health care facility. Secondary outcome measures included the number of ventilator-free days to day 28, organ-failure-free days to day 14, and ICU-free days to day 28. Conclusions The study was stopped because of futility after 745 of an estimated 1000 participants had been enrolled. There was no significant difference between study groups in 60 day in-hospital mortality or in mean ventilator-free days. The rosuvastatin group had fewer days free of hepatic or renal failure. Thus, rosuvastatin therapy did not improve clinical outcomes in participants with sepsis-associated ARDS and may have contributed to hepatic and renal organ dysfunction.

  Study phs003736

• Small cell number RNA-seq (400 cells per sample)

  Transcriptional profiles for stemB and proB cells harvested from either primary or secondary xenografts. This dataset contains six types of samples: - diagnostic stemB cells harvested from primary xenografts - diagnostic proB cells harvested from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with stemB cells from primary xenografts - relapse stemB cells harvested from secondary xenografts injected with proB cells from primary xenografts - relapse proB cells harvested from secondary xenografts injected with proB cells from primary xenografts

  Dataset EGAD50000001830

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 2.

  Dataset contains paired-end Whole Exome sequencing data from 257 glioma samples from 28 patients. 26 normal blood samples are also included.

  Dataset EGAD00001009496

• Whole-genome sequencing of cell-free DNA from pancreatic and breast cancer cohorts for fragmentomic and tumor fraction analysis

  This project provides whole-genome sequencing data from cell-free DNA collected from patients with pancreatic ductal adenocarcinoma and breast cancer, alongside healthy and benign controls. The study aims to identify novel liquid biopsy biomarkers by exploring the relationship between per-base quality scores and fragmentomic signals like end-motifs and fragment length. Furthermore, the data supports the development of Bayesian deep learning frameworks for the uncertainty-aware estimation of tumor fraction and ploidy in low-concentration clinical samples.

  Study EGAS50000001620

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination. Biological Materials were provided by the Ontario Tumour Bank, which is funded by the Ontario Institute for Cancer Research Reference for citation: Ling Liu, Jinghua Feng, Julian Polimeni, Manli Zhang, Hai Nguyen, Urmi Das, Xu Zhang, Harminder Singh, Xiao-Jian Yao, Etienne Leygue, Sam K.P. Kung, and Xie J. Characterization of cell free plasma methyl-DNA from xenografted tumours to guide the selection of diagnostic markers for early-stage cancers. Frontiers in Oncology, 2021 Feb. 5. DOI: 10.3389/fonc.2021.615821.

  Study EGAS00001006175

• 16S-based fecal microbiota composition

  The dataset reports the 16S rRNA gene sequencing of the fecal microbiota of donors from the Milieu Intérieur Cohort. The Milieu Intérieur cohort includes a total of 1,000 healthy individuals of western European ancestry, recruited in France as part of the Milieu Intérieur project. To assess their fecal microbiota composition, 16S rRNA profiles were generated from stool samples of 863 of the 1,000 donors. Human stool samples were produced at home no more than 24 hours before the scheduled medical visit and collected in a double-lined sealable bag maintaining strict anaerobic conditions. Upon reception at the clinical site, the fresh stool samples were aliquoted and stored immediately at -80°C. DNA was extracted from stool and barcoding PCR was carried out using indexed primers targeting the V3-V5 region of the 16S rRNA gene. Equal volumes of normalized PCR reaction were pooled and thoroughly mixed. The amplicon libraries were sequenced on Illumina MiSeq.

  Dataset EGAD00001004979

• Analysis of Cell-Free DNA to Predict Outcome to Bevacizumab Combination Therapy in Metastatic Colorectal Cancer Patients

  This dataset includes FASTQ files of low coverage whole genome sequencing of normal tissue (n = 8), tumor tissue (n = 55) and cell free DNA from plasma samples (n=101) from patients with metastatic colorectal cancer treated with bevacizumab. A total of 164 samples are present from two different cohorts. The first batch of samples (n = 139, sample names sAPD302T until sAPD502_P0) were collected from the AC-Angiopredict Phase 2 trial (NCT01822444), the second batch of samples (n = 25m, sample names sAPD503_P0 until sAPD527_P0) were collected from the UMM cohort.

  Dataset EGAD50000000176

• The Genomic Map of Poland in Open Access

  The main goal is to prepare and share WGS/WES of Polish population In this project NGS (next generation sequencing) was performed using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner was used. Shared BAM and BAM.BAI files Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Study EGAS50000000096

• LongVar low-coverage data

  This dataset includes sequencing data from participants of the LongVar study. Specifically, it comprises low-coverage whole genome sequencing (WGS) data which was derived from cell-free DNA from blood samples. These data were generated to compare imputation accuracy. 133 individuals agreed to share their data, and are healthy volunteers.

  Study EGAS50000001114

• Angiopredict: predicting response for bevacizumab treatment

  In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers worked with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to bevacizumab containing therapy. In this retrospective study, copy number profiles were determined using whole genome shallow sequencing, and progression free survival and treatment data was collected.

  Study EGAS00001002724

• MicroRNA profiling by next-generation sequencing for colorectal cancer screening

  The study was conducted as the marker discovery phase to identify potential microRNA (miRNA) candidates for colorectal cancer (CRC) screening. Genome-wide profiling with next-generation sequencing (NGS) was performed using plasma samples from 20 newly diagnosed CRC cases and 20 controls free of colorectal neoplasms matched by age and sex.

  Study EGAS00001005030

• Total RNA sequencing from the TNT trial (NCT00532727)

  Primary tumours from 186 TNT participants (13 matched recurrences) were profiled using total RNA-sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective-response-rate (ORR) and progression-free-survival (PFS) and performed conditional inference forest clustering to integrate multi-modal data.

  Study EGAS00001007398

• Label-free single-cell RNA Multiplexing leveraging Genetic Variability

  SNP-based demultiplexing of single-cell RNA-seq data

  Dataset EGAD50000000928

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• Measuring the level of relatedness between NGS datasets

  Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

  Study EGAS00001000600

• VIKING Health Study - Shetland

  The Viking Health Study – Shetland, together with ORCADES collectively termed VIKING, aims to identify genes influencing risk factors for common diseases such as heart disease, diabetes, glaucoma and stroke. The genetic research cohort study in Shetland was established to identify genetic variants, both common and rare, increasing risk of disease. This isolated population has a number of characteristics, the most important being the very large number of distant relatives, which are favourable for the identification of rare variants influencing disease risk. This study describes PCR-free paired end whole genome sequencing (TruSeq DNA PCR-Free, Illumina) run on a HiSeqX platform at 30X coverage on 500 individuals from VIKING. Unrelated individuals from the largest families were selected first, followed by those from smaller families, until eventually related individuals were selected to best represent the variation in the full cohort.

  Study EGAS00001003872

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination.

  Dataset EGAD00001008696

• FinaleMe: Predicting DNA Methylation by the Fragmentation Patterns of Plasma Cell-Free DNA

  Analysis of DNA methylation in cell-free DNA (cfDNA) reveals clinically relevant biomarkers but requires specialized protocols and sufficient input material that limits its applicability. Millions of cfDNA samples have been profiled by genomic sequencing. To maximize the gene regulation information from existing datasets, we developed FinaleMe, a non-homogeneous Hidden Markov Model (HMM), to predict DNA methylation of cfDNA and, therefore, tissues of origin directly from plasma whole genome sequencing (WGS). We validated the performance with 80 pairs of deep and shallow coverage WGS and whole genome bisulfite sequencing (WGBS) data from both cancer patients and healthy controls.

  Study phs003287

• Epigenomics of Prostate Cancer from Cell Free Plasma

  We sought to perform epigenomic characterization of prostate cancers by profiling circulating nucleosomes isolated from patient plasma using cell free chromatin immunoprecipitation followed by sequencing (cfChIP-seq). Our major findings include identification of prostate-cancer specific regulatory elements using a novel statistical method accounting for variable tumor DNA fraction in plasma, inferring transcription factor activity based on binding motif enrichment within regulatory elements, and epigenetically phenotyping patients based on clinical and genomic features. Data available in dbGaP will include cfChIP-seq and targeted sequencing from approximately 50 patients with a known diagnosis of cancer and healthy patient controls.

  Study phs003482

• Feasibility study of enzymatic methylation sequencing of cell-free DNA from cerebrospinal fluid of pediatric brain tumors for classification

  Array-based DNA methylation profiling is the gold standard for molecular classification of brain tumors. However, it relies on significant amount of input DNA extracted from surgical tissue, thus limiting its use for tumors where biopsy is challenging or limited in quantity. Cell-free tumor DNA (cfDNA) in cerebrospinal fluid (CSF) presents alternative opportunities for brain tumor diagnosis and disease monitoring following treatment. Novel enzymatic DNA methylation sequencing (EM-seq) methods may allow us to overcome input DNA limitations and accurately quantify methylation from cfDNA for tumor classification.

  Study EGAS50000000871

• Non-invasive prenatal diagnosis by genome-wide haplotyping of maternal cell-free plasma DNA

  Whereas non-invasive prenatal testing for aneuploidies (NIPT-A) is widely implemented, non-invasive prenatal testing for monogenic diseases (NIPT-M) is lagging. By capturing and targeted sequencing of 250000 polymorphic SNP loci from maternal plasma circulating cell-free DNA (cfDNA) and DNA from relatives, the fetal haplotype and chromosomal copy numbers are deduced. In all families tested, the cfDNA derived haplotypes are on average 97% concordant with the neonatal and embryo haplotype. This generic non-invasive prenatal diagnostic approach allows cost efficient scrutinizing the fetal genome for the presence of any inherited monogenic disease or trait.

  Study EGAS00001003634

• Dataset for NSCLC-RNA

  Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008846

• Dataset for liposarcoma-RNA

  Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008854