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• Biopsy-Derived Organoids in Personalised Early Breast Cancer Care: Challenges of Tumour Purity and Normal Cell Overgrowth Cap Their Practical Utility

  The ability to establish organoids composed exclusively of tumour rather than healthy cells is essential for their implementation into clinical practice. Organoids have in recent years emerged as a powerful tool to expand patient material in culture and generate modifiable 3D models derived from humans or animal models. For translational research, they enable the creation of model systems for an ever-increasing number of cell types and diseases. And in personalised medicine, they potentially allow for functional drug testing with high predictive power in certain settings. We found that using biopsy material from untreated, early-stage primary breast cancer patients poses significant challenges for consistently culturing tumour cells as organoids. Specifically, we observed frequent outgrowth of genetically normal, non-cancerous epithelial cells. We analysed >100 biopsy samples from early-stage breast cancer and present our large collection of >70 organoid lines. We also show methods of assessing successful tumour cell culture in a time and cost-efficient manner, proving a high rate (>85%) of normal cell overgrowth in early-stage breast cancer organoids. Finally, we show a number of successful attempts to culture cancer organoids from mastectomy-derived tissue of advanced, metastatic breast cancer. We conclude that the usefulness of organoids from early breast cancer for translational research and personalised medicine, especially guidance of adjuvant or post-surgical maintenance therapy, is strongly limited by the low success rate of culturing cancerous cells under organoid conditions.

  Study EGAS50000000605

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• Long read data generated for de novo assembly

  Long read data generated for de novo assembly (PacBio and ONT FASTQ files)

  Dataset EGAD50000002367

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas_LCM_

  Samples prepared by LCM - 5 cases for pilot study. Bulk DNA not available.

  Study EGAS00001003197

• Rhabdoid tumor sequencing data

  This study contains sequencing DNA and RNA sequencing data for rhabdoid tumors

  Study EGAS00001006351

• DATA FILES FOR SJRB

  DATA FILES FOR SJRB

  Dataset EGAD00001001045

• Dataset for "Genomic landscape of oral cancers" (Illumina RNA)

  Dataset for "Genomic landscape of oral cancers" (Illumina RNA)

  Dataset EGAD00001004366

• ChIPseq Sequencing data for epigenetic subgroups of meningioma

  Bam files for 16 meningioma tumor samples; ChIPseq performed on Illumina HiSeq 2000

  Dataset EGAD00001005021

• HLA sequence data and final calls for VaccGene and 1000Gp3 African populations

  HLA sequence data and final calls for VaccGene and 1000Gp3 African populations

  Dataset EGAD00001011379

• WES data for study of the microenviroment of angioimmunoblastic T-cell lymphoma

  Exome sequencing data for study of the microenviroment of angioimmunoblastic T-cell lymphoma

  Dataset EGAD00001011581

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• Comparison of Custom Capture for Targeted Next Generation DNA Sequencing

  Targeted, capture-based DNA sequencing is an economical way to sequence a customized region of the genome. Several targeted sequencing kits are available, but the efficacies of these kits have not been compared. We appraised four targeted DNA technologies for next generation sequencing, considering on-target sequencing, uniformity, and single nucleotide variation and copy number variation discovery. The technologies which utilized sonication to fragment genomic material showed impressive uniformity of capture. The other two had shorter preparation times, but sacrificed uniformity. One of those technologies, which needs transposase to fragment genomic material, has a weakness that requires all samples be pooled and the final one, which uses restriction enzyme digestion, is limited depending on restriction enzymes digest sites. Naturally, all technologies showed some concordance for calling SNVs, the kits that used restriction enzymes or transposase missed several SNVs, due, in large part, to lack of coverage. All technologies showed high integrity for copy number variant calling when compared to SNP arrays. This study aids laboratories in their decision of the proper technology to use for their intended applications.

  Study phs000811

• A Multi-Gene Mutation Classification of 468 Colorectal Cancers Reveals a Prognostic Role for APC

  Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinic-pathologic staging for decades. There is a need to molecularly stratify subpopulations of CRC to better predict outcome and assign therapies. Here we report targeted exome sequencing of 1,321 cancer-related genes on 468 tumor specimens, which identified a subset of 17 genes that best classify CRC, with APC (Gene ID: 324) playing a central role in predicting overall survival. APC may assume 0, 1, or 2 truncating mutations, each with a striking differential impact on survival. Tumors lacking any APC mutation carry a worse prognosis than single APC mutation tumors, but tumors with two APC mutations and KRAS (Gene ID: 3845) and TP53 (Gene ID: 7157) mutations confer the poorest survival among all the subgroups examined. Our study demonstrates a substantial prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

  Study phs001111

• The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR)

  The Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR) Registry and Repository, supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), was established in 2000 to provide a resource for the scientific community to explore genetic and non-genetic factors affecting rheumatoid arthritis (RA) occurrence and outcomes in African Americans. The long term objective is a database and a repository of 1,100 RA and 550 matched healthy African-American subjects. This CLEAR Registry and Repository has two arms: a longitudinal arm for subjects with early RA (enrollment from 2000 to 2005) and a cross-sectional arm for subjects with any disease duration (enrollment from 2006 to 2012). CLEAR has two components: a database and a repository. The database contains extensive demographic, socioeconomic, clinical and radiographic (radiographs of hands and feet) information and bone mineral density data from DEXA scans. The repository contains genomic DNA, plasma and serum on most of the participants. Participants in CLEAR II had RNA isolated from peripheral blood cells.

  Study phs001360

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

  Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R.

  Study phs002908

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Northern Manhattan Study (NOMAS)

  Cohort Description The Northern Manhattan Study (NOMAS) is a study of the population of Washington Heights in Northern Manhattan. The ongoing study, which began in 1990, has enrolled over 4,400 people, some of whom have suffered a stroke or related neurological syndromes. As the cohort aged, the specific aims grew to include not only vascular determinants of stroke but also cognitive decline, mild cognitive impairment (MCI) and dementia. The overall goal of NOMAS is to investigate stroke risk factors in different race-ethnic groups. NOMAS is also committed to developing better stroke prevention programs to improve the health of the community. The Hispanic population in Northern Manhattan is largely Dominican, along with Puerto Rican, Cuban, and Central and South American components.Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 887 NOMAS participants in C4R Wave 2 questionnaire data includes 448 variables for up to 815 NOMAS participants in C4R Derived data includes 43 variables for up to 995 NOMAS participants in C4R Phenotype data includes 113 variables for up to 995 NOMAS participants in C4R

  Study phs003028

• The Innate Immune Response as a Therapeutic Target for Cutaneous Leishmaniasis

  The overall goal of the proposed project is to identify innate host functions that contribute to cure or failure during antileishmanial drug therapy, and their related biomarkers. Results from this project enabled the identification of host-specific predictive and prognostic signatures of therapeutic responsiveness, and the bases for rational selection of host-targeted therapeutics that redirect inflammation and revert pathogenicity. Through sequential transcriptomic profiling of blood monocytes (Mo), neutrophils (Nφ), and eosinophils (Eφ) over the course of systemic treatment with meglumine antimoniate, we discovered that a heightened and sustained Type I interferon (IFN) response signature is a hallmark of treatment failure (TF) in Cutaneous Leishmaniasis (CL) patients. The transcriptomes of pre-treatment, mid-treatment and end-of-treatment samples were interrogated to identify predictive and prognostic biomarkers of TF. Results from this study instigate the evaluation of Type-I IFN responses as new immunological targets for host-directed therapies for treatment of CL, and highlight the feasibility of using transcriptional signatures as predictive biomarkers of outcome for therapeutic decision making.

  Study phs003545

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

  Determining response to therapy for patients with pancreatic cancer can be challenging. We evaluated methods for assessing therapeutic response using cell-free DNA (cfDNA) in plasma samples from 40 patients with metastatic pancreatic cancer as part of the CheckPAC trial (NCT02866383). Patients were evaluated before and after initiation of therapy using tumor-informed plasma whole-genome sequencing (WGMAF), and genome-wide cfDNA fragmentation profiles and repeat landscapes (ARTEMIS-DELFI). Of those assessed with WGMAF, molecular responders had a median overall survival (OS) of 319 days compared to 126 days for non-responders (HR=0.29, 95% CI=0.11–0.79, p=0.011). For ARTEMIS-DELFI, patients with low scores after therapy initiation had a longer median OS than patients with high scores (233 days versus 172 days, HR=0.12, 95% CI=0.046-0.31, p<0.0001). We validated ARTEMIS-DELFI in a separate cohort of 40 patients with pancreatic cancer who were part of the PACTO trial (NCT02767557). These analyses suggest that non-invasive mutation and fragmentation-based cfDNA approaches can identify therapeutic response of individuals with pancreatic cancer.

  Study EGAS50000000923

• BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology)

  The BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology) study is an ongoing longitudinal, population-based prospective birth cohort including 4,089 children born between 1994 and 1996 in Stockholm, Sweden. The cohort was initially designed to study risk factors for asthma, allergic diseases and lung function in childhood, and to study factors of importance for prognosis at already established disease.Questionnaires on respiratory symptoms and medication were answered at age of 1, 2, 4, 8 and 16 years. Response rates ranged from 96-82% at each occasion with very minor selection bias over the years. Exposure to air pollutants and other environmental factors has been mapped since birth.At the 8 and 16 year follow-up, spirometry and FeNO measurements were performed and at the latter, impulse oscillometry was measured. Blood samples (including plasma) from around 2,500 children were taken at 4, 8 and 16 years and have been analyzed for different IgE-ab and biomarkers. Genome-wide genetic, global methylation and transcriptomic data exist on a subset of the children.

  Study EGAS00001002746

• A combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancer

  The earlier diagnosis of cancer is one of the keys to reducing future cancer deaths. Here we describe our efforts to develop a non-invasive, blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinoma and 185 control patients without known cancers. KRAS mutations were detected in the plasma of 66 patients (30%) and every mutation found in the plasma was identical to that subsequently found in the patients' primary tumor (100% concordance). The use of KRAS in conjunction with two thresholded protein biomarkers (CA19-9 and prolactin) increased the sensitivity to 67%. Only one of the 185 plasma samples from the control cohort were positive for any of the three markers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

  Study EGAS00001002444

• An Isogenic Cell Line Panel for Sequence-based Screening of Targeted Anti-cancer Drugs

  We describe the creation and characterization of an isogenic cell line panel representing common cancer pathways, with multiple features optimized for high-throughput screening. More than 1,800 cell lines from three normal human cells were generated using CRISPR-technologies. Surprisingly, we discovered most of these lines did not result in complete gene inactivation, despite integration of sgRNA at the desired genomic site. However, a subset of the lines harbored true, biallelic disruptions of the targeted tumor suppressor gene, yielding a final panel of 100 well-characterize lines covering 19 pathways frequently subject to loss of function in cancers. This panel included genetic markers optimized for sequence-based ratiometric assays for drug-based screening assays. To illustrate the potential utility of this panel, we developed a multiplexed high-throughput screen that identified Wee1 inhibitor MK-1775 as a selective growth inhibitor of cells with inactivation of TP53. These cell lines and screening approach should prove useful for researchers studying a variety of cellular and biochemical phenomena

  Study EGAS00001005974

• Whole Exome Sequencing for Colorectal Cancer

  This project was designed to use next generation sequencing technology to screen the protein coding regions of the genome for low frequency variants in a panel of high-risk colorectal adenocarcinoma cases. Blood and cell-line DNA for colorectal cancer patients and a subset of quality control samples that had existing whole exome sequence data were analyzed using Illumina HiSeq sequencers. Samples from this project were from participants in the Women&#39;s Health Initiative (WHI) and the Diet, Activity, and Lifestyle Study (DALS).

  Study phs000410

• Circulating Tumor DNA Sequencing Provides Comprehensive Mutation Profiling for Pediatric Central Nervous System Tumors

  Tumor molecular profiling is increasingly important for the diagnosis and clinical management of childhood brain tumors, including diffuse midline glioma (DMG). We established a targeted deep sequencing approach using the TruSight Oncology 500 ctDNA exome panel to detect tumor genomic mutations and copy number variations in circulating tumor DNA from children diagnosed with DMG. In this study, we present the sensitivity, specificity, and clinical implications of our liquid biopsy sequencing approach for tumor genome profiling in children with DMG.

  Study phs003022

• ctDNA multigenic panel for non-small cell lung cancer

  Detection of actionable mutations in liquid biopsies constitute an important tool for management of non-small cell lung cancer (NSCLC) patients in the era of oncology precision medicine. We aimed to evaluate the actionable alterations using a commercial multi-gene panel in circulating tumor DNA (ctDNA) derived from plasma samples of treatment naïve and prior-treated non-small cell lung cancer (NSCLC) patients. For this, we analyze plasma samples of 30 subjects with non-small cell lung cancer.

  Study EGAS50000000643