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• HeartShare - Extant Datasets - Harmonized Clinical Trials Collection

  Heart failure with preserved ejection fraction (HFpEF) prevalence is rising with an aging population and contributing comorbidities, such as obesity and diabetes. The Get With The Guidelines - Heart Failure (GWTG-HF) study showed that the proportion of hospitalized HFpEF patients rose from 2005 to 2010, and this trajectory continued to increase through 2020. HFpEF patients have a poor 5-year outcome with a 75% mortality rate. Taken together, these data suggest that HFpEF may be the dominant HF subtype in the future, affecting approximately 1 in 10 adults during their lifetime.In addition to its increasing prevalence, HFpEF is a heterogeneous syndrome with multiple pathophysiological processes and varied clinical presentations. There is an urgent need to improve understanding of different HFpEF phenotypes to match patients with interventions based on their unique subtype. Phenomapping studies have identified between two and six HFpEF clusters/phenogroups with shared features. Of these, three overlapping phenotypes repeatedly arise: an 'older, vascular aging' phenotype, 'metabolic, obese' phenotype, and 'relatively younger, natriuretic peptide (NP) deficiency' phenotype. Continued refinement of these HFpEF subtypes is needed to identify distinct characteristics and underlying biologic and molecular mechanisms towards therapeutic development and future precision trials with improved diagnostic criteria and treatment including prevention.The HeartShare extant datasets collection consists of selected completed trials on HFpEF which have been harmonized for the purpose identifying and defining subtypes. The goal is to identify HFpEF subtypes that have a common pathophysiology. Through the HeartShare extant datasets collection, users can request access to both the harmonized data and the individual trial datasets.To request access to this study collection, select phs003989 in the dbGaP when submitting a data access request. The following clinical trials and harmonized data is available through this collection:Study NameHandleAccessionConsent GroupsSurgical Treatment for Ischemic Heart FailureBioLINCC_STICHphs003493.v1.p1GRUHeart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis TherapyBioLINCC_HFN_ATHENAphs003506.v1.p1GRUHeart Failure Network - Effectiveness of Ultrafiltration in Treating People With Acute Decompensated Heart Failure and Cardiorenal SyndromeBioLINCC_HFN_CARRESSphs003510.v1.p1GRUHeart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart FailureBioLINCC_HFN_DOSEphs003524.v1.p1GRUHeart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure PatientsBioLINCC_EXACT_HFphs003533.v1.p1GRUHeart Failure Network: Functional Impact of GLP-1 for Heart Failure TreatmentBioLINCC_HFN_FIGHTphs003542.v1.p1GRUHeart Failure Network - Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection FractionBioLINCC_HFN_NEATphs003548.v1.p1GRUHeart Failure Network - Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in Diastolic Heart FailureBioLINCC_HFN_RELAXphs003565.v1.p1GRUHeart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of DyspneaBioLINCC_HFN_ROSEphs003589.v1.p1GRUHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMBHeart Failure: A Controlled Trial Investigating Outcomes of Exercise TrainingBioLINCC_HF_ACTIONphs003599.v1.p1HMB-NPUGuiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart FailureBioLINCC_GUIDE_ITphs003621.v1.p1GRUSudden Cardiac Death in Heart Failure TrialBioLINCC_SCD_HeFTphs003654.v1.p1GRUTreatment of Preserved Cardiac Function Heart Failure With an Aldosterone AntagonistBioLINCC_TOPCATphs003665.v1.p1HMB-MDSHeart Failure Network - Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEFBioLINCC_HFN_INDIEphs003667.v1.p1GRUStudies of Left Ventricular DysfunctionBioLINCC_SOLVDphs003668.v1.p1GRUEvaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization EffectivenessBioLINCC_ESCAPEphs003782.v1.p1GRU

  Study phs003989

• 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

• eMERGE Geisinger eGenomic Medicine (GeM) - MyCode Project Controls

  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 patient 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. For the initial eMERGE Geisinger eGenomic Medicine (GeM) genotyping project, a subset of 1,232 unique samples were genotyped using Illumina HumanOmniExpress-12 v1.0 arrays, and used as population controls for other Geisinger Clinic case cohorts, including abdominal aortic aneurysm and gastric bypass surgery cases. These samples were selected from a larger subset of approximately 6,000 MyCode DNA samples using a partial matching algorithm that included age, sex, and body mass index as variables.

  Study phs000381

• Molecular_characterization_of_invasive_lobular_carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Study EGAS00001000292

• Evolving epigenomics of immune cells in type 1 diabetes at single nuclei resolution

  The appearance of diabetes-associated autoantibodies is the first detectable sign of the disease process leading to type 1 diabetes (T1D). Evidence suggests that T1D is a heterogenous disease, where the type of antibodies first formed imply subtypes. Here, we followed 49 children, who subsequently presented with T1D and 49 matched controls, profiling single-cell epigenomics at different time points of disease development. Quantitation of cell and nuclei populations as well as transcriptome and open-chromatin states indicated robust, early, replicable monocyte lineage differences between cases and controls, suggesting heightened pro-inflammatory cytokine secretion early among cases. The order of autoantibody emergence in cases showed variation across lymphoid and myeloid cells, potentially indicating cellular immune response divergence. The strong monocytic lineage representation in peripheral blood immune cells before seroconversion and the weaker differential coordination of these gene networks close to clinical diagnosis emphasizes the importance of early life as a critical phase in T1D development.

  Study EGAS50000000863

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• Next Generation Sequencing of Stage IV Squamous Cell Lung Cancers Reveals an Association of PI3K Aberrations and Evidence of Clonal Heterogeneity in Patients with Brain Metastases

  Putative oncogenic pathways in squamous cell lung cancer have been recently characterized, although their biologic repercussions in patients is largely unknown. This study sought to discover potential clinical manifestations of major pathways in squamous cell lung cancer, particularly the PI3K pathway. Two key findings emerged: patients with stage IV squamous cell lung cancer whose tumors harbored upstream PI3K aberrations had significantly worse survival and a higher burden of metastatic disease. In addition, brain metastases were significantly more common in these patients than in others. Paired lung primary/brain metastasis genotyping, including RNA sequencing and whole exome sequencing, uncovered a high degree of genetic heterogeneity between lung/brain pairs, and identified potential regulators of the metastatic process to brain.

  Study phs000907

• Spatial gene expression analysis of the tumor cells and their microenvironments at the pioneering-round of the metastasis.

  To analysis the metastatic process of invasive ductal carcinoma of the breast, we performed in situ gene expression analyses of the primary tumor, metastatic lympho node, and tumor-draining lympho node. To characterize the tumor, we also conducted multiomics analyses of normal breast tissue derived from the same patient.

  Study JGAS000804

• Molecular heterogeneity and commonalities in pancreatic cancer precursors with gastric and intestinal phenotype

  Due to the limited number of modifiable risk factors, secondary prevention strategies based on early diagnosis represent the preferred route to improve the prognosis of pancreatic ductal adenocarcinoma (PDAC). Here, we provide a comparative morphogenetic analysis of PDAC precursors aiming at dissecting the process of carcinogenesis and tackling the heterogeneity of preinvasive lesions.

  Study EGAS00001006793

• PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

  Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

  Study phs003985