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• Northwestern NUgene Project: Type 2 Diabetes

  The ability to correlate genetic variation with disease susceptibility and response to drug therapy depends on genotype or sequence analysis of large numbers of richly characterized DNA samples. Eight years agoWe are a part of NHGRI's electronic Medical Records and Genomics (eMERGE) Network, whose goal is to conduct genome-wide association studies in thousands of individuals using EMR-derived phenotypes and DNA from linked biorepositories. For eMERGE, Northwestern University (NU) is studying type 2 diabetes as a phenotype. In addition, in order to explore race differences in the prevalence of type 2 diabetes, NU collaborated with Vanderbilt University to study a mix of both Caucasian and African-Americans. Northwestern University: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. 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 questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) 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 phs000237

• Exceptional Responders Initiative

  The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

  Study phs001145

• Type 1 Diabetes Genetics Consortium (T1DGC): ImmunoChip Study

  The Type 1 Diabetes Genetics Consortium (T1DGC) was formed to address issues of limited sample size and consistency of phenotyping that had limited genetic investigations on risk of type 1 diabetes (T1D). The T1DGC first collected affected sib pair (ASP) families from four geographic networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, T1D cases and controls were ascertained from existing and de novo collections. The T1DGC assembled 2,601 T1D ASP families and 69 Parent-T1D offspring trios, T1D cases from the UK Genetic Resource Investigating Diabetes (UKGRID, N=6,670), and controls from the British 1958 Birth Cohort (B58BC, N=6,523), the UK National Blood Services collection (NBS, N=2,893) and the NIHR Cambridge Biomedical Research Centre BioResource (CBR, N=2,846). All samples included in this series have reported or self-declared European ancestry. All DNA samples were collected after approval from relevant institutional research ethics committees. Genotyping was performed using a custom Illumina Infinium high-density genotyping array, ImmunoChip (Illumina, Inc; CA) according to manufacturer's protocols. The ImmunoChip was designed to densely genotype, using 1000 Genomes and any other available disease specific resequencing data, immune-mediated disease loci identified by common variant GWAS. The ImmunoChip Consortium selected 186 distinct loci containing markers meeting genome wide significance criteria (P<5x10-8) from twelve such diseases (autoimmune thyroid disease, ankylosing spondylitis, Crohn's disease, celiac disease, IgA deficiency, multiple sclerosis, primary biliary cirrhosis, psoriasis, rheumatoid arthritis, systemic lupus erythematosus, T1D and ulcerative colitis). All 1000 Genomes Project pilot phase CEU population variants (Sept 2009 release) within 0.1cM (HapMap3 CEU) recombination blocks around each GWAS region lead marker were submitted for array design. No filtering on correlated variants (linkage disequilibrium) was applied. Additional content included regional resequencing data (submitted by several groups) as well as a small proportion of investigator-specific undisclosed content including intermediate GWAS results. After data cleaning and quality control, a total of 154,939 single nucleotide polymorphisms (SNPs) from 186 loci on ImmunoChip were scored. Case-control and family data were analyzed independently and combined by meta-analysis.

  Study phs000911

• Gabriella Miller Kids First (GMKF) Pediatric Research Program in Susceptibility to Ewing Sarcoma Based on Germline Risk and Familial History of Cancer

  Ewing sarcoma (EWS) is a deadly bone cancer that occurs in children and adolescents. Mounting evidence suggests that a genetic predisposition exists for this pediatric cancer, although the specific genetic contribution has yet to be identified. EWS has never been linked to a specific cancer predisposition syndrome, although several case reports have been published that describe siblings and cousins with EWS. Furthermore, neuroectodermal tumors appear to occur more commonly in families with EWS. The two consistent epidemiology findings in EWS include a very strong Caucasian predilection and increased rates of hernia in EWS patients and their family members. Finally, the role of genetic microsatellite repeats in EWS tumorigenesis has been recently described, and these GGAA microsatellites are polymorphic in repeat size and location across the genome. The study goals of this Kids First project include (1) To identify cancer predisposition genes in EWS trios increasing disease risk, (2) To identify genome-wide GGAA microsatellite repeats in EWS trios increasing disease risk, and (3) To identity de novo mutation and structural variant rates in EWS trios reflecting underlying DNA repair defects that increase disease risk. As part of the Kids First Common Fund initiative, this study proposal will further elucidate the genetic contribution to pediatric cancer development. Around 375 of these trios were selected for whole genome sequencing as part of the Gabriella Miller Kids First fund. The EWS trios have been collected as part of the Children's Oncology Group's AEPI10N5 Study ("Genetic Epidemiology of Ewing Sarcoma"), and each trio has associated phenotypic data including a detailed family history. We will interrogate the sequence data using our genomic analysis pipeline at the University of Utah and the Utah Science Technology and Research initiative's (USTAR) Center for Genetic Discovery. We will look for the genetic contribution to EWS and the sequence data with be shared in a repository designated by the Kids First Common Fund. The WGS of these ~375 EWS trios will help us to understand the genetic origins of a deadly childhood cancer and may lead to novel strategies for prevention and treatment.

  Study phs001228

• Identification of Modifiers of 22q11.2 Deletion Syndrome in Whole Genome Sequence - CIDR

  This project aims to identify genetic modifiers of congenital heart disease (CHD), which occurs among 22q11.2 deletion syndrome (22q11.2DS; also known as DiGeorge syndrome/velo-cardio-facial syndrome) patients. In contrast to the prevalence of ~0.8% in the general population, about 60%-70% of 22q11.2DS patients have CHD, of which most are conotruncal heart defects, making 22q11.2DS a very ideal model to study the genetic underpins of CHD. The chromosome 22q11.2 region is susceptible to meiotic chromosome rearrangements leading to hemizygous deletions, because there are large blocks of low copy repeats, termed LCR22s, that are dispersed in the region. Non-allelic homologous recombination during meiosis can lead to specific-sized deletions. Approximately 90% have a typical hemizygous 3 million base pair (Mb) deletion between LCR22-A and -D, while some have nested deletions between LCR22-A and B or LCR22-A and C. Our goal is to perform a case-control association study, in which cases have CHD, while controls have normal heart structures, all with 22q11.2DS. All individuals are unrelated and have been collected from collaborators in the US, Canada and Europe. All subjects received a clinical diagnosis of 22q11.2DS and signed informed consent to allow a blood sample to be collected for research. The DNA samples were de-identified in 2 steps to protect their privacy. We then determined deletion type using multiplex ligation-dependent probe amplification (MLPA). This information is provided for the great majority of subjects. We also obtained cardiac phenotype information from echocardiogram reports as well as reported race and ethnicity (Hispanic vs. non-Hispanic information), which is required for the analysis. We will obtain 30X whole-genome sequence data from NIH CIDR. We will first annotate the sequence variants identified to uncover rare ( For genotype data, we will provide the raw fastq data from whole-genome sequencing as well as the called variants file in a VCF file. For phenotype data, we will provide the sample relationship files (ped files), CHD affection status, deletion type, and race.

  Study phs002514

• Profiling Genome-Wide Circulating ncRNAs for the Early Detection of Lung Cancer

  Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Although imaging techniques such as low-dose computed tomography (LDCT), combined with tissue biopsies, have improved early detection rates, current diagnostic approaches are often limited by high false-positive rates, invasiveness, and radiation exposure, which lead to misdiagnosis and increased patient burden. Therefore, there is an urgent need for minimally invasive, accurate, and safe diagnostic biomarkers, particularly those derived from liquid biopsies such as blood-based exosomal RNA.This dataset specifically focuses on plasma-derived exosomal small non-coding RNAs (sncRNAs).A total of 233 de-identified plasma samples were obtained from Rush University Medical Center, including 116 NSCLC patients and 117 non-cancer controls. Exosomes were isolated from plasma, RNA was extracted, and small RNA sequencing was performed using the Illumina NextSeq 500 platform. Data available through dbGaP include individual-level raw sequencing files (FASTQ) and basic phenotype annotations of the plasma cohort.A diagnostic model was initially developed using small RNA-seq data from 1,446 tissue samples obtained from TCGA and GEO, identifying a robust sncRNA signature that distinguished NSCLC from non-cancer samples with an AUC of 0.90 in hold-out tissue validation. This signature was subsequently validated in the plasma exosome cohort, achieving an AUC of 0.84 in independent validation. The model demonstrated consistent diagnostic performance across subgroups stratified by age, sex, smoking history, cancer stage, and NSCLC subtype. Survival and functional analyses further supported the clinical and biological relevance of the identified sncRNAs. It is hoped that this resource will contribute to a better understanding of the sncRNA expression landscape in NSCLC and promote the development of non-invasive biomarkers for early cancer detection. These data may be applied to the investigation of transcriptomic and other risk factors, provide insight into cancer screening, tumor progression mechanisms, and prognosis prediction, and ultimately support precision medicine for NSCLC.

  Study phs004166

• Gabriella Miller Kids First Pediatric Research Program in Pediatric T-Cell Acute Lymphoblastic Leukemia

  The outcome for patients with relapsed T-ALL is dismal with 3-year event free survival of AALL0434 was a Children's Oncology Group-initiated phase 3 randomized clinical trial comparing Capizzi-style escalating methotrexate plus pegaspargase (CMTX) vs. high dose methotrexate (HDMTX), with/without six 5-day courses of nelarabine. Survival on this study was superior to any prior trial for de novo T-ALL, changing the standard of care. Yet, a substantial minority (~15%) of patients had relapsed or refractory (r/r) disease. Through the TARGET initiative, RNA sequencing (RNA-Seq), DNA copy number analysis, and whole-exome sequencing (WES) were performed on 264 T-ALL patients treated on AALL0434, demonstrating recurrent alterations could be grouped into 10 different potentially targetable functional pathways. This analysis was not powered to examine associations between genetic lesions with outcome, because too few patients with r/r disease were included. This project is dedicated to testing the hypothesis that comprehensive genomic profiling of the entire AALL0434 cohort will identify recurrent genetic alterations that can be segregated into biologically relevant deregulated pathways that can be combined with MRD to identify patients at risk for poor outcomes before they relapse and provide rationale for treatment with alternative therapies. In addition, a number of small recent studies demonstrated that many of the biologically relevant alterations in T-ALL occur in non-coding regions of the genome, but no large studies have performed whole genome sequencing (WGS) in T-ALL. This project also tests the hypothesis that WGS of a large cohort of patients with T-ALL will identify novel lesions in coding and non-coding regions that will be highly impactful in the understanding of T-ALL pathogenesis.These hypotheses are tested by performing comprehensive genomic profiling (WGS, WES, RNA-Seq, and copy number analysis) of the entire AALL0434 cohort with available samples with the following specific aims: (1) identify recurrent genetic alterations that predict poor outcome in T-ALL; (2) identify novel alterations, including non-coding alterations in T-ALL; and (3) identify germline genetic variants that predispose to T-ALL and to increased toxicity to chemotherapy.

  Study phs002276

• Barcoding reveals complex clonal dynamics of de novo transformed human mammary cells

  Most human breast cancers have already diversified genomically when they first become clinically evident, by which time extensive heterogeneous histopathologies, transcriptomes and growth patterns are also apparent. Accordingly, important initial events and the cellular context in which they occur have been difficult to characterize. Using DNA barcoding, we now demonstrate the high efficiency with which both purified basal and luminal cells isolated directly from normal adult human mammary tissue can be rapidly transformed by a single oncogene (KRASG12D) resulting in the production within 8 weeks in vivo of serially transplantable, polyclonal, invasive ductal carcinomas that are phenotypically heterogeneous and transcriptionally distinct from the initial cells transduced. Barcoding also revealed a consistent dramatic change in the clonal content of passaged tumours. This system thus provides a powerful new platform for examining early events in the genesis, evolution and treatment response of malignant human mammary cells generated using defined mutations.

  Study EGAS00001001310

• A novel TP53-KPNA3 translocation defines a de novo treatment-resistant clone in osteosarcoma

  Osteosarcoma is the most common primary bone cancer. It can be cured by aggressive surgery and chemotherapy, but outcomes for metastatic or chemoresistant disease remain dismal. Cancer sequencing studies have shown that the p53 pathway is dysregulated in nearly every case, often by translocation; however, no studies of osteosarcoma evolution or intratumor heterogeneity have been done to date. We studied a patient with chemoresistant, metastatic disease over the course of three years. We performed exome sequencing on germline DNA and DNA collected from tumor at three separate timepoints. We compared variant calls and variant allele frequencies between different samples. We identified subclonal driver mutations in several different genes in the primary tumor sample and found that one particular subclone dominated subsequent tumor samples at relapse. This clone was marked by a novel TP53-KPNA3 translocation and loss of the opposite-strand wild-type TP53 allele. Future research must focus on functional significance of such clones and strategies to eliminate them.

  Study EGAS00001001805

• Using de novo assembly to identify structural variation of complex immune system gene regions

  Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity. Several factors contribute to this including inheritable structural polymorphism of the underlying genes. To investigate this we generated data for a single healthy European individual (identified as HV31) using multiple long-read (PacBio Sequel II and Oxford Nanopore), short-read (Illumina HiSeq and MGI G400) and linked-read (10X Chromium and stLFR) sequencing platforms, and optical mapping using the Bionano Saphyr platform. DNA was extracted from monocytes or from peripheral blood mononuclear cells. We used these data to assemble a set of regions encoding components of the immune system and to investigate structural variation. The raw data and analysis results are deposited here for generate research use. A complete description of these data and results can be found in the accompanying article at https://doi.org/10.1101/2021.02.03.429586.

  Study EGAS00001005046