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• De Novo Characterization of Cell-Free DNA Fragmentation Hotspots in Plasma Whole-Genome Sequencing

  The raw sequencing data deposited here are low-coverage (~1X) whole-genome sequencing (WGS) of plasma cell-free DNA (cfDNA). The purpose is to validate the performance of early-stage cancer diagnosis in the Zhou et al. 2020 BioRxiv paper, mainly for two types of cancer: early-stage liver cancer and breast cancer. The cases and controls are matched with age, gender, smoking history, and alcohol usage. We developed a computational method to identify the cfDNA fragmentation hotspots from pooled low-coverage cfDNA WGS data. We found the cfDNA fragmentation hotspots are highly enriched in regulatory regions, such as open chromatin regions. The signals from these regions can help the diagnosis of early-stage cancers and their tissues-of-origin.

  Study phs003062

• cfDNAme allows early prediction of PE

  Preeclampsia (PE) is a leading cause for peripartal morbidity, especially if developing early in gestation. To enable prophylaxis to prevent PE, it is essential that pregnancies at risk of PE are identified early, in the first trimester. To identify patients at risk, we profiled methylomes of plasma-derived cell-free DNA (cfDNA) from pregnant women. We detected DNA methylation differences between control and PE pregnancies that enable risk stratification of patients, at PE diagnosis but also presymptomatically, around 12 weeks of gestation.

  Study EGAS00001007071

• Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy

  Anti-PD-(L)1 therapy is routinely used in metastatic NSCLC. However, response rates vary and biomarkers predicting treatment efficacy are lacking. Liquid biopsies allow monitoring of residual disease during therapy. Residual circulating tumor DNA (ctDNA) after therapy represents a predictive marker for adverse outcome. Here, we assessed copy number variations (CNVs) in serial plasma samples of NSCLC patients receiving PD-(L)1 blockade. We profiled CNV and fragmentation features in 118 plasma samples of advanced NSCLC patients by low-coverage whole genome sequencing taken at baseline, after four therapy cycles and at disease progression. CNVs and fragment features (i.e., fragment length, end motifs, position) were significantly altered in patients compared to healthy donors. Furthermore, fragment length changes at baseline and residual CNVs after four therapy cycles correlated with short progression-free survival. Our results highlight the suitability of plasma-based CNV and fragment analysis for disease monitoring and as a predictive marker for response duration in NSCLC patients under anti-PD-(L)1 therapy.

  Study EGAS50000000441

• A Somatic Reference Standard for Cancer Genome Sequencing

  In this study, we separately performed PCR-free whole genome sequencing on the paired tumor/normal melanoma COLO-829 and lymphoblastoid COLO-829BL cell lines across three separate institutions (TGen, Illumina, Genome Sciences Centre at the British Columbia Cancer Agency). We performed a meta-analysis of all data, in combination with the originally reported analysis of these cell lines by Pleasance et al., and report a somatic reference standard based on consensus events. This standard can be used as a reference for tumor/normal whole genome analyses.

  Study phs000932

• Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma

  Low Pass Whole Genome Sequencing of Cell Free DNA from Patients Receiving CD19 CAR T-Cell Therapy for Large B-Cell Lymphoma consisting of 123 samples with FASTQs with hg19 aligned BAM/BAI files.

  Dataset EGAD00001009175

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

  Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing (WGS) data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional and mutation type specific frequencies in tissue and cell-free DNA (cfDNA) of cancer patients that were associated with replication timing and other chromatin features. A machine learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of lung cancer patients, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches, and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

  Study EGAS00001007248

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

  The dataset for “Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer” includes 496 cram files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include tumor tissue, matched buffy coat and longitudinal plasma samples from individuals with pancreatic cancer.

  Dataset EGAD50000001353

• Characterization of CNS Metastases

  Metastatic disease to the central nervous system (CNS) is devastating, with a poor prognosis. There are limited treatment options for patients with CNS metastases, and in particular with leptomeningeal carcinomatosis (LMD). In this study, we evaluated the molecular and cellular features of parenchymal brain metastases and LMD. We used single-cell RNA and cell-free DNA profiling of CSF from patients with LMD receiving immunotherapy to demonstrate shifts in the liquid LMD tumor microenvironment. We also characterize the tumor microenvironment of parenchymal brain metastases using single cell sequencing, before and after treatment with immunotherapy.

  Study phs002416

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Cardiology Biobanking for Biomarker Discovery

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfThe BioHEART study is a multi-center, prospective, observational cohort study to identify new biomarkers in stable coronary artery disease (CAD) and acute myocardial infarction (MI) (ACTRN12618001322224). Participants are recruited at time of clinically indicated computed tomography (CT) coronary angiogram (CTCA). 1,950 of 5,000 planned participants have been recruited and serum/plasma/erythrocytes/monocytes stored, with follow-up ongoing. CTCA imaging studies provides volumetric quantification of total calcified and non-calcified plaque, which is assessed using established and novel scoring systems. Comprehensive molecular phenotyping is performed on blood samples using state-of-the-art genomic, transcriptomic, proteomics, metabolomic, lipidomic, and immunophenotyping. Outcome data will be used to build improved risk models for CAD.Reference: http://www.anzctr.org.au/ - ACTRN12618001322224

  Study phs002726

• Genome-wide cell-free DNA biological patterns in patients with cancer

  The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

  Study EGAS00001007400

• Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL)

  Enteropathy associated T cell lymphoma (EATL) is frequently preceded by a state of refractoriness to the gluten-free diet, called “refractory celiac disease” or RCD. We aim to study which mutations and copy number aberrations are already manifest in RCD and to identify differences between RCD patients that do, and do not, develop EATL. We have applied whole exome sequencing to detect mutations and copy number aberration predictive for progression from RCD to EATL.

  Study EGAS00001006669

• The dataset for Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  The dataset for “Detection of brain cancer using genome-wide cell-free DNA fragmentomes” includes 310 bam files from whole genome next-generation sequencing on the Illumina Novaseq 6000. The dataset analyzed include plasma cfDNA samples from patients with cancer, patients with neurological conditions, and healthy individuals.

  Dataset EGAD50000001445

• EGA QuickView

  EGA QuickView Secure and Remote Access to EGA Files What is EGA QuickView? EGA QuickView is a FUSE file system that allows secure and remote access to EGA files. It is a hybrid of sshfs and crypt4ghfs, which means it uses ssh to connect to the EGA distribution servers, downloads data in Crypt4GH format, and transparently decrypts those files. It is compatible with Linux and macOS 12. Why use EGA QuickView? EGA QuickView is a highly useful and convenient tool for anyone who needs to access EGA files remotely and securely. The software offers a quick and convenient way to browse through EGA files without the need for complete downloads, thus saving bandwidth and time. Whether you are a medical professional requiring access to sensitive patient data or a research scientist working on a project that involves EGA files, EGA QuickView provides a highly useful solution. The software boasts advanced security features, ensuring that your data is safe and protected at all times. Get started with EGA QuickView To get started with EGA QuickView, visit the EGA QuickView GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/ega-quickview

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Genetic and Phenotypic Determinants of Blood Pressure and Other Cardiovascular Risk Factors

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules. Source: ccdg.rutgers.edu The GAPP study is an ongoing national population-based prospective cohort study conducted in the Principality of Liechtenstein. Between 2010 and 2014, all inhabitants of Liechtenstein aged 25-41 years old were asked to participate in the study, and 2170 could be enrolled. The aim of the study is to identify the determinants of blood pressure and other cardiovascular risk factors and their progression over time. A large number of baseline characteristics and health information as well as several blood, urinary and genetic markers were collected. The samples were sent to The Broad Institute of MIT and Harvard to generate genetic data using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.

  Study phs002236

• A prospective multicenter study of plasma ctDNA versus archival tumor tissue to guide FGFR-targeted therapy in metastatic urothelial cancer - Targeted

  Targeted sequencing data related to the publication titled "A prospective multicenter study of plasma ctDNA versus archival tumor tissue to guide FGFR-targeted therapy in metastatic urothelial cancer." FGFR alterations, seen in up to 25% of metastatic urothelial carcinoma, can be exploited with targeted therapy. Here, we perform targeted sequencing of cell-free DNA, archival FFPE, and white blood cell DNA to compare ctDNA versus tissue for FGFR biomarker status and monitor temporal changes to FGFR over the disease course, specifically after progressing on targeted therapy.

  Study EGAS50000001450

• Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

  This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

  Study EGAS00001004942

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

  The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer includes 57 BAM files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010891

• Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

  Here, we performed genome-wide 5-mC profiling in plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis and therapy monitoring. Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples were available from previous studies.

  Study EGAS00001006573

• NLG-LBC-05 ctDNA

  Correlative analysis of circulating tumor DNA (ctDNA) in aggressive large B-cell lymphoma patients treated in NLG-LBC-05 phase II trial. Whole genome and targeted sequencing was applied to longitudinal plasma cell-free DNA and diagnostic tumor tissues.

  Study EGAS00001005835

• DAC for cell free DNA TAPS study

  Dac EGAC00001001903

• The dataset for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  The dataset for “Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers” includes 409 cram files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000000695

• 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

• Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors

  Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of various cancers but its utility in renal cell cancer (RCC) has not been well established. A combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n=90) with various renal tumour subtypes, were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of ~33% for both cohorts. A highly sensitive personalised approach, applied to plasma and urine from select patients (n=22), improved detection to ~50%, including in patients with early stage and even benign lesions. A machine-learning based model, applied to untargeted data, predicted this detection, potentially offering a means of triaging patient samples for personalised analysis. We observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than a single tissue biopsy. Longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. These data highlight low ctDNA levels in RCC but indicate potential clinical utility provided improvement in isolation and detection approaches.

  Study EGAS00001003530

• Children's Hospital of Philadelphia (CHOP) Control Copy Number Variation (CNV) Study

  We present a database of copy number variations (CNVs) detected in 2,026 disease-free individuals, using high-density, SNP-based oligonucleotide microarrays. This large cohort analyzed for CNVs in a single study using a uniform array platform and computational tools, comprises mainly of Caucasians (65.2%) and African-Americans (34.2%), We have catalogued and characterized 54,462 individual CNVs, 77.8% of which were identified in multiple unrelated individuals. These non-unique CNVs mapped to 3,272 distinct regions of genomic variation spanning 5.9% of the genome; 51.5% of these were previously unreported, and >85% are rare. Our annotation and analysis confirmed and extended previously reported correlations between CNVs and several genomic features such as repetitive DNA elements, segmental duplications and genes. We demonstrate the utility of this data set in distinguishing CNVs with pathologic significance from normal variants. Together, this analysis and annotation provides a useful resource to assist with the assessment of CNVs in the contexts of human variation, disease susceptibility, and clinical molecular diagnostics. The CNV resource is available at: http://cnv.chop.edu. Reprinted from Shaikh T., et al., High-Resolution Mapping and Analysis of Copy Number Variations in the Human Genome: A Data Resource for Clinical and Research Applications Genome Research. 2009, with permission from Genome Research. CHOP CNVs from 2,026 disease-free individuals are available through dbVar at http://www.ncbi.nlm.nih.gov/dbvar/studies/nstd21.

  Study phs000199

• Carolina Breast Cancer Study (CBCS)

  The Carolina Breast Cancer Study (CBCS), phase III, is a population-based study aiming to understand the social and molecular correlates of breast cancer outcomes, particularly among Black and young women. CBCS recruited first primary breast cancer cases from 44 North Carolina counties between 2008-2013. All cases were between age 20 and 74 and self-identified as female. Black women and young women were systematically oversampled by randomized recruitment such that the study includes approximately 50% Black women and approximately 50% women diagnosed before age 50. A total of 2,998 participants were enrolled. In the ten years following diagnosis, women completed surveys approximately every 1-2 years and diagnoses of subsequent distant local recurrence and second primary tumors were ascertained via linked medical records. We identified records of women who developed secondary breast tumors (including second primary tumors, contralateral breast cancers, and locoregional recurrences), and these participants were oversampled for targeted DNA sequencing using the UNCseq panel (~1200 genes).CBCS germline pathogenic mutations cannot be investigated because participants were consented between 2008 and 2013 with specific language prohibiting this. However, germline data can be used to call somatic mutations or to standardize somatic genomic data.For sharing of study data not included here, please visit unclineberger.org for instructions on submitting a data use agreement.

  Study phs003725