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• Single cell targeted DNA-sequencing (and antibody sequencing) of high hyperdiploid B-ALL

  This dataset contains all sequencing data of the publication "Single-cell DNA and Surface Protein Characterization of High Hyperdiploid Acute Lymphoblastic Leukemia at Diagnosis and During Treatment". We provide both the raw fastq-files as well as the processed data in the form of .h5 files. There are 13 patients: XJ176, XH135, XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162, XF98, XG111 and XG115. Of 9 patients, also follow-up samples during/after treatment were sequenced: XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162 and XG111. To identify the cell types and distinguish between normal and leukemic cells, cell surface proteins were also captured for 6 samples: XF98, XG111 (at diagnosis and during treatment), XG115, XI162 (after treatment) and XJ175 (after treatment). All samples were processed on the MissionBio platform with a custom amplicon panel, and DaB-seq for the combined targeted DNA and protein sequencing.

  Dataset EGAD50000000829

• fragmentomic features of individuals with different cfDNA concentrations

  The uploaded data includes sequencing data of 862 individuals from the nasopharyngeal carcinoma (NPC) screening study. Samples from this cohort were sequenced using targeted sequencing methods for the Epstein Barr Virus (EBV) and selected autosomal DNA, but only ‘off-target’ reads were used for fragmentomic analyses. We have also performed genome-wide (non-targeted sequencing) for 1) Individuals with the highest and lowest cell-free DNA concentration (40 individuals); 2) A subsequent collection of the subjects with the highest and lowest DNA concentrations after six years (26 individuals); 3) 30 cases of pregnancy and 4) 20 patients with hepatocellular carcinoma. All sequencing data are of extracted plasma cfDNA from human subjects. The targeted sequencing samples from 862 individuals were sequenced on the NextSeq500 System (Illumina) and aligned to the EBV genome (AJ507799.2) and the human genome (hg19). The alignments were provided in bam format. The original fastq files of the remaining non-target sequencing samples were provided.

  Dataset EGAD50000000970

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• IMCISION RNAseq

  RNA sequencing of 32 primary head and neck squamous cell carcinoma (HNSCC) samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy, and 30 paired on-treatment HNSCC samples (i.e. after neoadjuvant immunotherapy). RNA quantity used: 10ng. Library Preparation Kit: SMART Stranded Total RNA Seq Kit (Takara). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ

  Dataset EGAD00001008127

• 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

  Dataset EGAD00001007793

• Metabolic reprogramming towards OXPHOS identifies a novel therapeutic target for mantle cell lymphoma

  Metabolic reprogramming is linked to cancer cell growth and proliferation, metastasis, and therapeutic resistance in a multitude of cancers. Targeting dysregulated metabolic pathways to overcome resistance, an urgent clinical need in all relapsed/refractory cancers, remains difficult. Through genomics analysis of clinical specimens, we show that metabolic reprogramming towards oxidative phosphorylation (OXPHOS) and glutaminolysis is associated with therapeutic resistance to the Bruton’s tyrosine kinase inhibitor ibrutinib in mantle cell lymphoma (MCL), an incurable B-cell lymphoma with poor clinical outcomes. Inhibition of OXPHOS with a novel, clinically applicable small molecule, IACS-010759, which targets complex I of the mitochondrial electron transport chain, results in significant growth inhibition in vitro and in vivo in ibrutinib-resistant patient-derived cancer models. This work suggests that targeting metabolic pathways to subvert therapeutic resistance is a clinically viable approach to treat highly refractory malignancies.

  Dataset EGAD00001004577

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• eMERGE Network Imputed GWAS for 41 Phenotypes

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of ten participating sites (Cincinnati Children's Hospital Medical Center/Boston Children's Hospital, Children's Hospital of Philadelphia, Essentia Institute of Rural Health, Marshfield Clinic Research Foundation and Pennsylvania State University, Geisinger Clinic, Group Health Cooperative/University of Washington, Mayo Clinic, Icahn School of Medicine at Mount Sinai, Northwestern University, Vanderbilt University Medical Center) funded by the NHGRI to investigate the use of electronic medical record (EMR) systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 55,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of over forty phenotypes, including Abdominal aortic aneurysm; Ace-Inhibitor/Cough; Attention Deficit Hyperactivity Disorder; Age-related macular disease; Appendicitis; Asthma; Atopic Dermatitis; Autism; Benign Prostatic Hyperplasia; Carotid artery disease as a Quantitative Measure; caMRSA; Cataract; Clostridium difficile colitis; Extreme Obesity; Chronic Kidney Disease; Chronic Kidney Disease and Type 2 Diabetes; Chronic Kidney Disease, Type 2 Diabetes and Hypertension; Colon Polyps; Cardiorespiratory Fitness; Dementia; Diverticulosis; Diabetic retinopathy; Gastroesophageal Reflux Disease; Glaucoma; Height; Heart failure; Hypothyroidism; Lipids; Ocular hypertension; Peripheral Arterial Disease; QRS duration; Red blood cell indices; Remission of Diabetes after ROUX-EN-Y gastric bypass surgery; Resistant hypertension; MACE while on Statins; Type 2 Diabetes; Venous Thromboembolism; White blood cell indices; and Zoster virus infection, as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. Sites and participants include: Children's Hospital of Pennsylvania (CHOP): The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic medical records (EMRs). EMRs are longitudinal, with a mean duration of 6.5 years. Cincinnati Children's Hospital Medical Center/Boston's Children's Hospital (CCHMC/BCH): Cincinnati Children's Hospital Medical Center (CCHMC) and Boston Children's Hospital (BCH) are pediatric institutions dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. The CCHMC/BCH site has been built on a five-year history of collaboration, particularly in patient electronic record (ERM)-related informatics, the basis of much of eMERGE II. CCHMC and BCH together bring an extraordinary faculty to eMERGE II who are committed to diseases that afflict children, specifically phenotypes that focus upon diseases of children in ways that will leverage the available eMERGE adult GWAS and EMRs to discover meaningful use results. CCHMC/BCH plans to demonstrate real-time execution of phenotypic selection across their two distinct pediatric institutions as a model for ensuring phenotypic standardization and for national scalability. They will also look carefully at parents' responses to results and use of their children's research results and better understand the factors that influence their decisions about learning incidental findings. In addition to patient and parent perceptions CCHMC/BCH will also explore clinician perceptions of pharmacogenetic research results after EMR integration. Geisinger Health System: A research cohort of adult Geisinger Clinic patients was enrolled from community-based primary care clinics of the Geisinger Health System. Patients were eligible for enrollment if they were a primary care patient of a Geisinger Clinic physician and were scheduled for a non-emergent clinic visit. All participants provided written informed consent and HIPAA authorization. Consenting patients agreed to provide blood samples for broad biomedical research use, and permission to access data in their Geisinger electronic medical record for research. The enrollment rate was 90% of patients approached. The demographics of the cohort approximate those of the Geisinger Clinic outpatient population. Research blood samples were collected during an outpatient clinical phlebotomy encounter. Research blood samples are coded and stored in a central biorepository. Samples are linkable to clinical data in a de-identified manner for research via an IRB-approved data broker process. For genomic analysis, DNA is extracted from EDTA-anticoagulated whole blood. Group Health(GH)/University of Washington (UW): GH participants for the PGx project were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N~6300.) Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in GH's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at Group Health: 1. Demographics - participants with self-reported race as Asian or African ancestry were prioritized and selected to enrich for non-European ancestry; 2. Diagnosis and procedure codes - participants were selected if found to have a history of hypertension, atrial fibrillation (AF), or congestive heart failure (CHF). Participants with a history of arrhythmia were added if the entire selection algorithm did not generate 900 individuals. We also enriched for participants with EHR evidence of actionable indications related to PGRNSeq genes. Participants were selected if found to have an ICD9 code for malignant hyperthermia, hypertension, atrial fibrillation, congestive heart failure or long QT syndrome (LQTS); 3. Laboratory values - if participants had any laboratory event of creatine kinase (CK) >1000, and were dispensed statins within 6 months of the event, then they were selected; and 4. Medications - participants were excluded if ever on carbamazepine or had a current regimen of warfarin. Essentia Institute of Rural Health, Marshfield Clinic, Pennsylvania State University (Marshfield): The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG , was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR. Icahn School of Medicine at Mount Sinai School (Mt. Sinai): The Institute for Personalized Medicine (IPM) Biobank Project is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM Biobank populations include 28% African American (AA), 38% Hispanic Latino (HL) predominantly of Caribbean origin, 23% Caucasian/White (CW). IPM Biobank disease burden is reflective of health disparities with broad public health impact: average body mass index of 28.9 and frequencies of hypertension (55%), hypercholesterolemia (32%), diabetes (30%), coronary artery disease (25%), chronic kidney disease (23%), among others. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites, waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations.

  Study phs000888

• Genetic Causes of Growth Disorders

  Description of the disorder: A very common disorder presenting to pediatricians/pediatric endocrinologists is childhood growth failure. Sometimes the cause is evident, for example, growth hormone deficiency. In other children, the etiology remains unknown despite extensive evaluation, resulting in the unhelpful diagnosis of severe idiopathic short stature (SISS). These conditions are quite heterogeneous, including children with isolated growth failure and others who also have other abnormalities such as developmental delay or a constellation of congenital anomalies (syndromic short stature). Sometimes, the disorder appears to primarily affect the growth plate, which drives skeletal growth and thereby determines overall body proportions, whereas in other children, the disorder affects skeletal and non-skeletal tissues equally. Some cases of SISS have a polygenic inheritance while others appear to follow a Mendelian inheritance model, recessive, dominant or X-linked. Very recently, genome-wide analysis for copy number variants (CNVs) and whole-exome sequencing have begun to identify some of the molecular etiologies of these disorders.1 Identifying the molecular etiology of growth disorders has clinical and scientific value. Clinically, identifying a molecular cause prevents extensive further testing and may direct anticipatory care for associated medical problems. For example, we recently studied aggrecan (ACAN) gene mutations in families with autosomal dominant short stature and accelerated skeletal maturation. These mutations affect both growth plate cartilage, causing linear growth failure, and also articular cartilage, causing osteochondritis dissecans and early-onset osteoarthritis.1 Etiological classification of idiopathic growth failure allows more precise characterization of prognosis and response to treatment, which are currently highly imprecise because of the locus heterogeneity. In some cases, finding the genetic etiology points to a novel treatment approach that targets the specific molecular pathway involved. The proposed project is central to the main focus of our group, the Section on Growth and Development, NICHD. Our primary goal is to investigate cellular and molecular mechanisms governing childhood growth and to gain insight into the many human genetic disorders causing childhood growth failure. The proposed project is well suited for the intramural program because it takes advantage of Clinical Center expertise to phenotype subjects with SISS. Study subjects: We will study subjects with SISS and nuclear family members. SISS will be defined by height SDS < -2.5 for age without evident cause after routine evaluation including: growth hormone axis evaluation; thyroid function testing; celiac disease screening; urinalysis; CBC; chemistry; karyotype (girls, for Turner syndrome); and testing for single gene defects based on the clinical evaluation (for example, SHOX or Noonan-associated genes). Candidate families will include isolated growth disorders and growth disorders that are accompanied by congenital anomalies, developmental delay, or other syndromic short stature. Strong preference will be given to subjects with a severe phenotype and a pedigree that indicates a Mendelian inheritance. Multiple independent families with the same phenotype will have priority. The pool of applicants for recruitment is large, and we receive many inquiries by emails and phone consultations from pediatric endocrinologists for advice regarding diagnosis and management of unusual growth disorders, including familial disease. Often these families are seeking further evaluation and are willing to participate in a research study. From this pool, we will be selecting pedigrees with very favorable Mendelian characteristics, for example de novo dominant occurrences where two normal parents have a child with SISS, and the child grows up to be an adult who passes this phenotype on to multiple grandchildren in the next generation. Subjects and family members will be brought to the NIH Clinical Center (NIHCC) for outpatient evaluation. Participants will be evaluated by pediatric endocrinology fellows (as part of our training program) and by senior staff to establish the clinical findings and construct a pedigree. Subjects will receive additional biochemical and imaging studies at the Clinical Center to complete the phenotyping and assign affected status. The growth abnormality will be evaluated by assessing body proportions, relative organ size, and skeletal imaging as indicated. Associated clinical abnormalities beyond altered growth will be characterized with the help of other Clinical Center subspecialists. Subjects and family members will be evaluated by SNP microarray and whole-exome sequencing. We anticipate 4-5 persons for each of 16-20 families, for a total of 72-90 whole-exome sequences. Half of the families will be recruited and studied within the first year and half in the second year. We will use freshly collected peripheral blood as the DNA source for SNP array and NextGen Sequencing. Analytic approach: The candidate genes will be chosen based on 1) inheritance state consistency, 2) population frequency in the ESP and UDP databases, and 3) predictions of deleteriousness. We will use VarSifter and the B road Institute Integrated Genome Viewer to filter and visualize these data. The genetic model will be dependent on the family's pedigree. For a simple trio, we will explore variants using genetic models including autosomal recessive, de novo (dominant), compound heterozygous, deletion/point mutation recessive, and X-linked (male only). The candidate variants will be identified using Boolean logic sets in VarSifter following intramural NHGRI/UDP methods. We will also use SNP microarray data to identify copy number variations, complete/single copy deletions, duplications, non-paternity, consanguinity for homozygosity mapping, uniparental isodisomy, mosaicism, and segregation patterns (bed file generation for use in VarSifter filter work). After a list of candidate sequence variants has been generated, annotation will include using the Exome Variant Server, Polyphen-2, MutationTaster, Sift, and CADD predictions of deleteriousness. Biological laboratory data will be included to prioritize candidate variants. Our group has expertise in the molecular mechanisms regulating both skeletal growth2,3 and growth of other tissues4,5, which may be helpful in this phase of the analysis. The most promising candidate mutations will be confirmed by Sanger sequencing and studied functionally, in vitro and/or in vivo. For mutations that affect skeletal growth, we will use experimental systems related to growth plate cartilage. For in vitro studies, we have experience transfecting chondrocyte cell lines, such as ATDC5, and primary chondrocytes. We will determine whether the mutation alters protein and/or cell function. In vivo studies can be used to explore pathophysiology. We have recently successfully used a new approach, the CAS9/CRISPR system to knockout multiple loci in mice (unpublished), which can be used again in the future to create mouse models efficiently. 1J Clin Endocrinol Metab, 2014 (PMID: 24762113) 2J Mol Endocrinol, 2014 (PMID: 24740736) 3Hum Mol Genet, 2012 (PMID: 22914739) 4Proc Natl Acad Sci U S A, 2013 (PMID: 23530192) 5Endocr Rev, 2011 (PMID: 21441345)

  Study phs001617

• Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

  Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (> 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

  Study EGAS00001004878

• Single_Cell_Sequencing_of_Sperm__scSperm_

  The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

  Study EGAS00001000935

• Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

  Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects from a 10-year prospective study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as subclonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of genetic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident “pseudoantralized” subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

  Study EGAS00001007067

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• STAMPEED: Northern Finland Birth Cohort 1966 (NFBC1966)

  The Northern Finland Birth Cohorts program (NFBC) was initiated in the 1960s in the two northernmost provinces of Finland to study risk factors involved in pre-term birth and intrauterine growth retardation, and the consequences of these early adverse events on subsequent morbidity and mortality. The uniqueness of NBFCs is that the data of the cohorts were obtained from early fetal life (including maternal health during pregnancy) to adulthood. The NFBC1966 includes 12,058 live births to mothers in the two northern-most provinces of Finland. Two decades later, a second cohort of 9432 births was obtained (NFBC1986). In NFBC1966 pregnancies were followed prospectively from the first antenatal contact (10-16th week). After birth, the offspring were examined and then again underwent clinical evaluation at ages 1y, 7y, 14-16y and 31y. At each visit, a wide range of phenotypic, lifestyle and demographic data were gathered by questionnaires and clinical examinations. For the most part, NFBC1986 has undergone similar evaluations to NFBC1966. Linkage to national registries includes hospitalization, deaths, education, medication, pensions, and provides up-to-date demographic and clinical information for members of both cohorts. DNA samples were obtained from 5,923 subjects from NFBC1966 and 6688 subjects from NFBC1986. Data coverage, 96% of all births in 1966 and 99% in 1986, is highly representative for the whole population. The NFBC program comprises more than 20 different projects coordinated by the Center of Lifecourse Disease studies in Northern Finland (COLD) at Oulu University. The prospective data collected from the NFBCs form a unique resource, allowing the study of disease emergence, and of the importance of genetic, biological, social and behavioral risk factors. The genome-wide association (GWA) study sponsored through the STAMPEED program of NHLBI employed genomic DNA samples previously collected by the NFBC1966 study and stored in the DNA repository of the National Institute for Health and Welfare, Finland. This NHLBI sponsored RO1 project aimed to identify genetic variants contributing to metabolic and cardiovascular diseases (CVD). In addition to de-identified genome wide genotypic data, a selected list of phenotypic data related to CVD including weight, height, BMI, HDL, LDL, total cholesterol, triglyceride, glucose, insulin and fasting status, are also available in dbGaP. A summary of the GWAS for the NFBC1966 cardiovascular risk traits can be found in Sabatti et al., Nature Genetics 41: 35-46, 2009, PMID: 19060910. The version 2 release of this study contains sequence data from seventeen loci associated with levels of triglyceride, HDL-C, LDL-C, total cholesterol, fasting plasma glucose, and fasting plasma insulin (Kathiresan et al. 2008, Willer et al. 2008, Sabatti et al. 2009, Dupuis et al. 2010, Teslovich et al. 2010). At each locus, protein-coding regions and 5' and 3' untranslated regions of genes nearest to single nucleotide polymorphisms showing genome-wide significant association with metabolic syndrome-related traits, were sequenced. Targeted Illumina sequencing of 78 genes (~270kb) using 150bp probes was performed on 4943 subjects of the Northern Finland Birth Cohort 1966 (NFBC1966). Whole exome sequencing on the Illumina platform was carried out on 586 of those participants. The sequencing study is part of a larger project that is funded by the National Human Genome Research Institute's Allelic Spectrum in Common Disease Initiative, and comprises sequence data from more than 7000 individuals in two Finnish cohorts: NFBC1966 and the Finland-United States Investigation of NIDDM Genetics (FUSION) study.

  Study phs000276

• Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP): COVID-19 Testing and Prevention in Correctional Settings

  This study will work with diverse correctional facilities across MN, RI, WA, and FL to characterize the incidence of COVID-19 disease progression and related outcomes. The goal is to identify barriers and facilitators to develop strategies to improve testing in these under-served populations by: Increasing the reach, access, uptake, and impact of COVID-19 testing among incarcerated people and staff in prison and jails. Individuals in congregate settings have been disproportionately affected by COVID-19, with correctional settings accounting for 39 of the 50 largest cluster outbreaks in the country to date. Schema of Correctional Facilities: Correctional facilities are amplifiers of infectious diseases for structural reasons: 1) Dormitory-style living and overcrowded conditions make social distancing nearly impossible 2) They have a focus primarily on security not health 3) Their medical departments are under-resourced and often disconnected from local public health agencies. Correctional facilities must be the focus of urgent intervention to understand the incidence of COVID-19, how it spreads in correctional facilities, and durable long-term strategies to reduce transmission, including testing and vaccines. However, our work from the COVID Prison Project shows that correctional systems have implemented a range of testing strategies, without coordination, such that synthesizing the information on COVID-19 incidence, outcomes and optimal testing strategies (including repeat testing and contact tracing) has been challenging. Incarcerated people decline testing due to concerns about confidentiality, implications for release, and fear of placement in solitary confinement. Through interviews we will identify ethical concerns and potential solutions for COVID-19 testing and vaccine strategies in correctional facilities using a community-engaged strategy. The project's work from the COVID Prison Project shows that correctional systems have implemented a range of testing strategies, without coordination, such that synthesizing the information on COVID-19 incidence, outcomes and optimal testing strategies (including repeat testing and contact tracing) has been challenging. Incarcerated people decline testing due to concerns about confidentiality, implications for release, and fear of placement in solitary confinement. Through interviews we will Identify ethical concerns and potential solutions for COVID-19 testing and vaccine strategies in correctional facilities using a community-engaged strategy. Goals: 1. Identify ethical concerns and potential solutions for COVID-19 testing and vaccine strategies in correctional facilities using a community-engaged strategy. 2. Characterize incidence of COVID-19, disease progression, and related-outcomes and effectiveness of testing and contact tracing in correctional facilities. Participant Selection: a. Potential subjects must be currently incarcerated at key facilities in Washington, Rhode Island, Minnesota, and Florida. These facilities are Everglades Correctional Institution and Homestead Correctional Institution in Florida, Shakopee and Stillwater correctional facilities in Minnesota, the Rhode Island Department of Corrections, and Yakima County Jail in Washington. b. Participating correctional facilities in Florida, Minnesota, Rhode Island, and Washington will provide de-identified data on approximately 16,859 incarcerated adults and correctional staff. Data sources include deidentified data from medical records, administrative data, and policy documents pertaining to COVID-19. c. 3 series of focus groups (6, 12, 18 months) x 3 distinct groups (incarcerated people, medical providers, and correctional leaders) x 4 sites=36 total focus groups over the study period. d. Will utilize 74,812 COVID-19 tests to test and re-test a total of 16,859 incarcerated people and correctional staff for active infection over a six-month period in the FL, MN, and RI state prison systems and the Yakima County Jail in WA.

  Study phs003361

• Ongoing Replication Stress Tolerance and Clonal T Cell Responses Distinguish Liver and Lung Recurrence and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

  Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) survive longer when disease spreads to the lung but not to the liver. We generated overlapping, multi-omic datasets to identify molecular and cellular features that distinguish patients whose disease develops liver metastasis (liver cohort) from those whose disease progression results in lung metastasis without liver metastases (lung cohort). Lung cohort patients generally survived longer than liver cohort patients, independent of tumor subtype. We developed a pORG gene signature that distinguishes primary tumors in the liver and lung cohorts. We identified ongoing replication stress (RS) response pathways in high pORG/liver cohort tumors, while low pORG/lung cohort tumors had greater densities of lymphocytes and shared T cell clonal responses. Our study demonstrates that liver-avid PDAC is associated with tolerance to ongoing RS, limited tumor immunity, and less favorable outcomes; whereas low RS, lung-avid/liver-averse tumors are associated with active tumor immunity that may account for favorable outcomes. As expected, we found high frequencies of KRAS, TP53, CDKN2A, and SMAD4 gene alterations in our tumor samples. High pORG activity (GSVA scores) in our primary tumors appear to be positively correlated with alteration frequencies in both TP53 and CDKN2A. We did not see a correlation with alterations in KRAS as almost all the tumor samples have KRAS alterations. From a de-identified dataset of 1,873 patients diagnosed with and/or treated for PDAC at our institution between 2004 and 2020, we identified 422 patients for which we had specimens with sequencing data (N=374) and/or specific evidence of disease metastasis site(s) from the OHSU cancer registry or disease-relevant computed tomography (CT) scans to allow cohort classification. Note that our study includes RNA-Seq, DNA-Seq panel, and TCR-Seq (T-cell Receptor Sequencing) data, but that this dbGaP submission just includes the patients/samples with RNA-Seq and/or DNA-Seq panel data. Therefore, this submission includes 290 samples from 278 patients. TCR sequence data is available on the Adaptive Biotechnologies platform. Clinical course timepoints, patient demographics, stage, grade, nodal involvement, resection margins, and angiolymphatic invasion were provided as deidentified data by the OHSU cancer registry with quality control data verification in a subset by pathologists (BB and TM). We reviewed all available computed tomography (CT) scans for all patients with primary tumor resection dates recorded by the cancer registrar, with tumor samples analyzed by RNA-seq, DNA-seq, or TCR-seq, and/or with additional information indicating metastatic spread (e.g., metastatic samples received for related studies). We abstracted the site of all lesions proven to be metastatic by biopsy and/or that clearly increased in size during progression or decreased in size during treatment as long as a radiologist described the lesion as “likely”, “suspicious for”, “concerning for”, or “favor” metastasis. Clinical imaging was reviewed by a radiologist (AG) to validate patient assignments to the liver, lung, and neither liver nor lung (other recurrence site) cohorts. Time to recurrence was calculated from the earliest of either the recurrence date provided by the OHSU cancer registry, or the date of earliest lesion abstracted from CT reports. The subject attributes reported in this submission were up to date at the time of our data freeze, which occurred July 2021.

  Study phs003597

• Exome sequencing reveals pathogenic variants in known and novel candidate genes for severe sperm motility disorders

  STUDY QUESTION: What are the causative genetic variants in patients with male infertility due to severe sperm motility disorders? SUMMARY ANSWER: We identified high confidence disease-causing variants in multiple genes previously associated with severe sperm motility disorders in 9 out of 21 patients (43%). We also identified variants in novel candidate genes in 8 additional patients (38%). WHAT IS KNOWN ALREADY: Severe sperm motility disorders are a form of male infertility characterised by vital, but immotile sperm often in combination with a spectrum of structural abnormalities of the sperm flagellum. Examples of this spectrum of disorders include dysplasia of the fibrous sheath / multiple morphological abnormalities of the sperm flagella (DFS-MMAF) and severe forms of asthenozoospermia associated to non-specific structural defects. These disorders frequently recur in families and may include chronic respiratory disease. As such, genetic causes are suspected and many genes have recently been reported. Currently, depending on the clinical sub-categorisation, up to 50% of causality in patients with severe sperm motility disorders can be explained by pathogenic variants in at least 21 known genes. STUDY DESIGN, SIZE, DURATION: We performed exome sequencing in patients with severe sperm motility disorders from two different clinics, aiming to identify the underlying genetic defects and establishing a diagnostic yield in both. PARTICIPANTS/MATERIALS, SETTING, METHOD: Two groups of infertile men, one from Argentina (n= 9) and one from Australia (n=12), with clinically defined sperm motility disorders were included. All patients in the Argentine cohort were diagnosed with DFS-MMAF, based on transmission electron microscopy. Exome sequencing was performed in all 21 patients and variants with an allele frequency of <1% in the gnomAD population were prioritised and interpreted. MAIN RESULTS AND ROLE OF CHANCE: In 9/21 patients (43%), we identified pathogenic variants in known sperm motility disorder genes: CFAP43 (3 patients); CFAP44 (2 patients), QRICH2 (2 patients), DNAH1 (1 patient) and DNAH6 (1 patient). The diagnostic rate did not differ markedly between the Argentinian and the Australian cohort (44% and 42%, respectively). Furthermore, we identified patients with variants in the novel candidate sperm motility genes CFAP58, DNAH12, DRC1, MDC1, PACRG, SSPL2C and TPTE2. One patient presented with two possibly damaging variants in four candidate genes and it remains unclear which variants were responsible for the severe sperm motility defect in this patient. LIMITATIONS, REASONS FOR CAUTION: In this study, we described patients with potential bi-allelic variants in known and novel candidate genes for severe sperm motility disorders. Due to unavailability of parental DNA, we have not assessed de novo or maternally inherited dominant variants and could not phase the mutations to establish in all cases that the mutations occur on both alleles. WIDER IMPLICATIONS OF THE FINDINGS: Our results confirm an important role for five known genes for sperm motility and we demonstrate that exome sequencing is an effective method to diagnose patients with severe sperm motility defects (9/21 diagnosed; 43%). Furthermore, our analysis revealed seven novel candidate genes for severe sperm motility disorders. Genome-wide sequencing of additional patient cohorts and re-analysis of exome data of currently unsolved cases may reveal additional variants in these novel candidate genes.

  Study EGAS00001005018

• Oncogenic Ectodomain deletion of FGFR1 caused by Breakage-Fusion-Bridges in Squamous Cell lung Cancer

  The identification of recurrent 8p11.23 amplifications including FGFR1 raised the hope of a treatable target in squamous cell lung cancer (SQLC). However, only a minority of patients with FGFR1-amplified tumors respond to single agent inhibitor therapy targeting FGFR. To understand the underlying mechanism of FGFR1 dependency, we performed whole genome and transcriptome sequencing of 25 FGFR1-amplified primary tumors with unknown response upon FGFR inhibition. In addition, we performed deep sequencing of 26 FGFR1-amplified samples whereof the response upon FGFR inhibition was known for 25 samples. In both cohorts we identified intra-chromosomal tail-to-tail breaks close to the FGFR1 transcription start site, being responsible for focal amplification of FGFR1. These specific breaks are caused by a Breakage-Fusion-Bridge-like (BFB-like) mechanism. Here, we associate these breaks with FGFR inhibitor sensitivity. Moreover, in some cases these breaks are located within the open reading frame of FGFR1, which leads to the expression of an ΔEC-FGFR1 transcript that lacks the ecto-domain. Overexpression of ΔEC-FGFR1 transforms Baf3 cells and lead to an FGFR1-dependent phenotype. Our results demonstrate that the truncation of the FGFR1 ectodomain is a frequent event in 8p11.23-amplified squamous cell lung cancer caused by tail-to-tail breaks. These breaks might be used as a predictive therapeutic marker to stratify patients for FGFR-inhibitor therapy.

  Study EGAS00001005059

• Neoadjuvant immune checkpoint blockade in mismatch-repair proficient colon cancers

  Immune checkpoint blockade has led to paradigm shifts in the treatment of various tumour types, yet limited efficacy has been observed in patients with metastatic mismatch-repair proficient (pMMR) colorectal cancer. Here we report an in-depth analysis of patients with early-stage pMMR colon cancer from the phase II NICHE study (ClinicalTrials.gov: NCT03026140). A total of 31 patients received neoadjuvant treatment of nivolumab plus ipilimumab followed by surgery. The response rate was 26% and included six patients with a major pathological response (≤10% residual viable tumour). One patient with an ongoing clinical complete response did not undergo surgery. Responses were observed despite a low tumour mutational burden in all tumours, while chromosomal genomic instability scores were significantly higher in responders compared to non-responders. Responding tumours were more likely to be TP53 mutant, KRASG12 wildtype and had significantly higher baseline expression of proliferation signatures and TCF1. Imaging mass cytometry also revealed a higher percentage of Ki-67+ cancer and Ki-67+ CD8+ T cells in responders compared to non-responders. Meanwhile, in non-responders, we observed an enrichment for an inflamed-fibrotic microenvironment associated with TGF-β expression, hinting towards possible resistance mechanisms. These results provide a comprehensive analysis of response to neoadjuvant ICB in early-stage pMMR colon cancers and identify potential biomarkers for patient selection.

  Study EGAS50000000856

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

  The majority of ovarian cancers are diagnosed at an advanced stage and have a high mortality rate. Current screening strategies fail to improve prognosis because markers of early stage disease are lacking. This medical need justifies the search for biomarkers enabling early detection of ovarian cancer. In this study, we explore the extracellular transcriptome of utero-tubal lavage fluid obtained from 26 ovarian cancer patients and 48 controls using messenger RNA (mRNA) capture and small RNA sequencing. Because of its contact with the fallopian tube and the ovaries, collection of utero-tubal lavage might be the preferred non-invasive method to identify localized lesions compared with analyses based on peripheral blood samples. We observed an enrichment of ovarian and fallopian tube specific messenger RNAs in utero-tubal lavage fluid compared to other human biofluids. Over 300 mRNAs and 41 miRNAs were upregulated in ovarian cancer samples compared with controls. Upregulated genes were enriched for genes involved in cell cycle activation and proliferation, hinting at a tumor derived signal. In conclusion, we provide proof-of-principle that mRNA capture sequencing of utero-tubal lavage fluid is technically feasible, and that the extracellular transcriptome of utero-tubal lavage should be further explored in larger cohorts to assess the diagnostic value of the biomarkers identified in this study.

  Study EGAS00001005498

• Cell-free DNA fragmentation patterns and personalized sequencing reveal circulating tumor DNA in urine and plasma of glioma patients

  Glioma-derived cell-free DNA (cfDNA) is challenging to detect using liquid biopsy as levels in body fluids are low. We determined the glioma-derived DNA fractions in tumor biopsies, in cerebrospinal fluid (CSF), plasma and urine samples, using deep sequencing of personalized capture panels. By sequencing cfDNA across thousands of mutations identified individually in each patient’s matched tumor we detected tumor-derived DNA in plasma (10/12) and urine samples (8/11). The median tumor fraction was 6.4x10-3 in CSF, 3.1x10-5 in plasma and 4.7x10-5 in urine. We identified a shift in the size distribution for mutant cfDNA fragments in these body fluids. Next, we analyzed cfDNA fragment sizes with paired-end shallow whole genome sequencing (WGS) in urine samples from 35 patients with gliomas, 8 individuals with non-malignant brain disorders, and 26 controls (n=69 individuals, 96 samples). cfDNA in urine of glioma patients was significantly more fragmented compared to urine from patients with non-malignant brain disorders (t-test, p=1.7x10-2) and compared to urine of controls (t-test, p=5.2x10-9). The proportion of DNA fragments <60 bp was higher in glioma patients urine and could be used for classification (AUC=0.93). Machine learning models integrating fragment lengths could identify urine samples from glioma patients (AUC=0.97 in cross-validation).

  Study EGAS00001004355

• Single cell sequencing of a post-PD-1 inhibitor metastatic melanoma mass

  Three technical replicates of FACS-sorted T cells (CD45+CD3+) and one replicate of FACS-sorted tumor cells (MCSP+) were loaded to a targeted 10,000 cells per lane on the 10X Genomics Chromium Controler with the single cell 5’ Immune Repertoire and Gene Expression profiling kit. In total, we loaded ~30,000 individual tumor infiltrating lymphocytes (TILs) and ~10,000 melanoma cells on the 10X platform (10X Genomics, CA, USA). Reverse transcription, TCR enrichment, and library preparations were performed according to the 10X Genomics 5’ V(D)J protocol revision C. Transcriptome libraries were pooled and sequenced on the Illumina NovaSeq 6000 S2 flow cell with 26 R1, 8 i7, and 91 R2 cycles respectively. The TCR libraries were pooled and sequenced on the Illumina MiSeq V2 150 cycles paired-end. Single cell transcriptomic and TCR data was processed with the 10X Genomics Cell Ranger Pipeline version 2.2.0 with the software-provided GRCh38 reference transcriptomes. After quality control, there was RNAseq profile data available from 6267 immune and 4303 melanoma cells. Downstream processing and visualization was encompassed through Seurat and tSNE plots.

  Dataset EGAD00001006013

• Paired-WGS Sequencing of Primary lymphomas of the central nervous system (PCNSL)

  26 Tumor/Control pairs of WGS data of PCNSL tumors, sequenced on either Illumina HiSeq2000/2500 instruments or HiSeq X Ten. The controls are blood or buffy coat samples in most cases.

  Dataset EGAD00001007806