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• RNA-Seq of Whole Blood from Pediatric Sickle Cell Anemia (SCA) Patients

  The aim of this study is to define the immune cell transcriptome by next generation RNA sequencing in blood from individuals with SCA, in comparison to healthy African American controls. This study has a cross-sectional case-control design. We will compare the transcriptome profiles of blood mononuclear cells from healthy age-matched African American children without cardiovascular disease or risk factors (“Controls”) to those of children with SCA, age 5 -21 years, who are not receiving chronic red blood cell transfusions or hydroxyurea therapy to identify genes that are differentially expressed in SCA. 

  Study phs002687

• Whole_exome_sequencing_of_young_onset_Primary_Sclerosing_Cholangitis

  Primary sclerosing chloangitis is a rare autoimmune disease of the liver (prevalence =10/100,000) with a mean age of onset of 40 years. We are currently undertaking GWASand immunochip experiments to identify loci underlying PSC susceptibility. Through ourcollaborators at the University of Calgary we have access to DNA from three parent-offspringtrios where the children required liver transplants due to PSC before the age of 9. These areextremely rare cases indeed and we believe that exome-sequencing represents a powerfulmeans of identifying the causal mutation underlying this severe phenotype.

  Study EGAS00001000388

• AVENIO Expanded ctDNA panel sequence alignments (BAMs)

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 100 plasma samples from patients with lung cancer undergoing treatment in the OSCILLATE trial. After 150 bp paired-end sequencing, reads were aligned to the human genome reference with the AVENIO Oncology Analysis Software. These files are the sorted non-deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD50000000138

• Prognostic factors in prostate cancer: deep sequencing pilot project TAPG

  This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

  Dataset EGAD00001001237

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• Targeted sequencing of Burkitt lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  The UK’s Haematological Malignancy Research Network (www.HMRN.org) was established in 2004 to provide robust generalizable data to inform clinical practice and research. HMRN is a collaboration between researchers in the Epidemiology & Statistics Group (ECSG) at the University of York, a unified Clinical Network operating across 14 hospitals, and an integrated Haematological Malignancy Diagnostic Service (HMDS) in Leeds. Covering a population of around 4 million, HMRN collects detailed information about all patients diagnosed with a haematological malignancy within the HMRN region, accruing around 2,400 new diagnoses each year. The population has a similar socio-demographic profile to the country as a whole, and HMRN’s maturing data present an increasingly valuable resource to address real questions of concern to haematologists, commissioners and health service researchers – locally, nationally and internationally. This study forms part of a larger project employing targeted exome sequencing on tumour samples from patients diagnosed with a variety of both lymphoid and myeloid malignancies. The results for samples collected from 39 Burkitt lymphoma patients, diagnosed within HMRN from 2005 to 2012, are provided.

  Study EGAS00001004649

• NHLBI GO-ESP: Family Studies (JHMI-Molecular Genetics of Atypical Cystic Fibrosis (CF) Study)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Cystic fibrosis (CF) patients without detectable disease-causing mutations in CFTR present a clinical phenotype very similar to, but possibly discrete from, classic CF. We hypothesize that the phenotype of these atypical CF patients is not due only to mutations in the carbonic anhydrase gene CA12 or in the genes encoding the epithelium sodium ion channel ENaC, but is due to mutations in novel genes that have yet to be associated with CF. The goal of this study is to determine the molecular etiology of this atypical CF.

  Study phs000556

• The ITCC-P4 PDX platform of pediatric cancers for preclinical testing

  Cancer is the leading cause of disease-related deaths among children in high-income countries. Tumor heterogeneity and lack of mechanism-of-action-based therapeutic options are key challenges to overcome in order to improve pediatric cancer patients’ survival. Here, we report the EU-IMI-2 funded public-private partnership “ITCC-Pediatric Preclinical Proof-of-Concept Platform” (ITCC-P4), which has built a large repertoire of patient-derived xenograft (PDX) models, representing all major solid pediatric cancer types, for in vivo drug testing. Three-hundred-fifty-three PDX models from diagnostic and relapsed pediatric cancers have been established and molecularly characterized, together with matched germline/tumor samples. As proof-of-concept, we present in vivo drug screening data in neuroblastoma and rhabdomyosarcoma models. PDX data, accessible at http://r2platform.com/itcc-p4, allow the selection of models based on oncogenic drivers and/or potential biomarkers for preclinical testing. Operated by a non-profit entity (www.itccp4.com), this sustainable platform aids academic and industrial researchers in developing and prioritizing innovative therapies for pediatric cancer.

  Study EGAS00001008330

• Extent and Significance of Bacterial DNA Integrations in the Human Cancer Genome

  The integration of exogenous DNA into the human genome can cause somatic mutations associated with oncogenesis. For example, the insertion of HPV DNA into human chromosomes is the single most important event leading to tumorigenesis in cervical cancer. It is also now preventable with vaccines against HPV. In contrast to viral DNA integrations, the instances and repercussions of bacterial DNA integration into the somatic human genome are less clear. Yet bacterial DNA integrations (BDI) found to be associated with tumorigenesis could also be prevented using therapeutics like vaccines that limit exposure to the bacteria. Previous analysis of publicly available sequencing data from the Cancer Genome Atlas (TCGA) showed BDIs from Pseudomonas spp. rRNA into the 5'-UTR of four proto-oncogenes as well as in Ig (the immunoglobulin gene) of gastric cancer samples. The original samples from TCGA were not available to validate these findings. Therefore, a different cohort of gastric cancer patients was identified in order to establish the presence BDIs. Whole exome sequencing was completed on seven tumor samples and six adjacent gastric samples, as well as one intestinal metaplasia sample and one non-atrophic gastritis sample. Four of those samples were also investigated with transcriptomics and whole genome sequencing. Given that 15-20% of cancers worldwide are linked to infections, more work is needed to understand the role of infectious agents in oncogenesis and the mechanisms underlying that role.

  Study phs001936

• Successful Clinical Response in Pneumonia Therapy (SCRIPT)

  The goal of this study is to iteratively identify, validate and refine biomarkers to predict clinical failure, and identify novel targets for therapy, beyond traditional antibiotics, for patients with severe pneumonia requiring intubation, including severe community-acquired pneumonia (CAP), hospital-acquired pneumonia, and ventilator-associated pneumonia (HAP/VAP). We hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution.The major emphasis will be on HAP. Mechanically ventilated CAP patients are a very high-risk group for subsequent VAP, and therefore CAP samples will be included to determine baseline bacteria, microbiome, and host defense patterns for those that do or do not develop HAP/VAP. Hospital-acquired pneumonia is the leading cause of death from nosocomial infections. Even in patients receiving pathogen-appropriate therapy, reported clinical failure rates are increasing, approaching 50% in recent clinical trials. Current approaches to improve outcomes in patients with pneumonia almost exclusively focus on the development of antibiotics to address the problem of resistance. However, the prevalence of antibiotic-resistant pathogens is insufficient to explain the high rates of clinical failure. Instead, we hypothesize that factors within the alveolar microenvironment in many patients with pneumonia prevent the active process of pneumonia resolution. These factors include pathogen-specific adaptations to the injured lung that modulate the innate and adaptive immune response, as well as changes to the alveolar microbiome, driven by selective pressure within our modern intensive care units. Understanding this complex adaptive system requires the integration of clinical information with unbiased measures of the host, pathogen, and microbiome changes within the alveolar microenvironment. These measures must be repeated over time to identify factors that distinguish successful from failed therapy for pneumonia sufficiently early during the clinical course to allow for effective interventions. To address this challenge, we have assembled a talented group of investigators in the Successful Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center. We will leverage our routine clinical practice of safe alveolar sampling in mechanically ventilated patients with pneumonia with repeated non-bronchoscopic bronchoalveolar lavage (NBBAL) sampling over the course of pneumonia. From this fluid, we will combine flow cytometry with multi-omic technologies (cell population-specific transcriptomics, epigenomics, shotgun microbiome sequencing, and pathogen-specific sequencing). Our systems scientists will integrate these genomic data with robust clinical -omics with the goal of identifying biomarkers that can be prospectively tested in patients and causally evaluated in humanized mouse models.The addition of a pooled sample artificially increases the number of automatically computed subjects by one.

  Study phs002300