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• Genomic Characterization CS-MATCH-0007 Arm Z1B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with CCND1, CCND2, and/or CCND3 amplifications are treated with Palbociclib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002180

• NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II)

  This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180.

  Study phs000920

• Gene Variants in Pheochromocytoma and Paraganglioma

  Pheochromocytoma and paraganglioma (PPGL) are rare neuroendocrine tumors that arise from chromaffin cells in the adrenal medulla and in extra-adrenal locations, respectively. PPGL has the strongest hereditary risk of all endocrine neoplasms with about 40% of cases harboring germline mutations and another 25-30% of cases arising from somatic mutations. To date, over 20 susceptibility genes have been suggested to play a role in PPGL pathogenesis, with more genes still being researched. This project will seek to identify new candidate genes in apparently sporadic PPGLs to reveal a possible genetic background in cases without variants in known susceptibility genes. Knowledge of the genetic background and the genes involved in the pathogenesis of PPGL allows for clustering and/or development of targeted therapies for the tumors that cannot be surgically resected or tumors that have metastasized.

  Study phs002405

• Genomic Alterations and Transcriptional Phenotypes in Circulating Tumor DNA and Matched Metastatic Tumor

  We analyzed a prospective cohort of 49 plasma samples obtained before, during, and after treatment from 20 patients with recurrent small cell lung cancer. We conducted cfDNA low-pass whole genome sequencing (0.1X coverage) and exome sequencing (130X coverage) in comparison with time-point matched tumor characterized using whole-exome (130X) and transcriptome sequencing. A direct comparison of cfDNA and tumor biopsy revealed that cfDNA not only mirrors the mutation and copy number landscape of the corresponding tumor, but also identifies clinically relevant resistance mechanisms and cancer driver alterations not detected in matched tumor biopsies. Longitudinal cfDNA analysis reliably tracks tumor response, progression, and clonal evolution. Sequencing coverage of plasma DNA fragments around transcription start sites showed distinct treatment-related changes and captured the expression of key transcription factors n the corresponding SCLC tumors.

  Study phs003689

• Methylation-Based Immune Deconvolution in Prostate Cancer Patients Before and After Radical Prostatectomy

  To explore whether surgical treatment for prostate cancer leads to long-term immune changes, we conducted a pilot study of n=11 prostate cancer patients treated with radical prostatectomy. We also included n=8 patients managed with active surveillance as a comparison group. We examined intra-individual changes in circulating immune cell subsets using serial blood samples collected pre- and approximately 6-months post-prostatectomy, and from matched time points for the patients managed on active surveillance. Immune cell subsets were deconvoluted using genome-wide methylation data. We observed no meaningful changes in circulating immune cell subsets in either patient group, suggesting that any surgery-induced immune changes to the circulating immune profile may not be long-lasting. The genome-wide methylation data from the two time points will be made available through dbGaP.

  Study phs003660

• Spatiotemporal Charting of Human Esophageal Development for Epidermolysis Bullosa Cell Therapy

  Human fetal esophageal development is not well understood. We present a spatio-temporal single-cell multi-omics atlas to close such a long-standing knowledge gap. With such an atlas, we describe the cellular heterogeneity and lineage transitions of esophageal epithelium and stroma. We delineate the cellular dynamics of both epithelial and stromal populations during the establishment of esophageal tissue architecture. We identify niche paracrine signals that drive the development of the epithelium. We develop an in silico perturbation deep learning algorithm to further enlighten the in vitro derivation of esophageal basal cells (eBCs) and we use the algorithm to screen for effective and efficient signaling pathway perturbations that could guide in vitro eBC differentiation. We observe that chemically perturbing prioritized pathways yields functional eBCs. Such success sheds light on cell replacement therapy of eBC dysfunction, such as Epidermolysis Bullosa.

  Study phs003281

• Next Generation Sequencing to Predict Risk of Events from Coronary Artery Disease

  Coronary artery disease (CAD) and myocardial infarction (MI) remain the leading cause of death worldwide and in the US. In recent years, clinical studies that considered intermediate phenotypes (phenotypic or genomic data isolated between DNA and the main disease phenotype) have greatly enhanced our understanding of complex traits like CAD by enabling inference of biological networks from the combination of genetic and genomic datasets isolated from disease-relevant tissue(s). The NGS-PREDICT study used whole transcriptome sequence data generated from primary macrophages derived in vitro from venous blood that was obtained from CAD cases and non-CAD controls. This study provided a valuable resource for the validation of biomarkers identified in STARNET NGS data from macrophages obtained from patients with and without CAD. It also can be used as a reference dataset for the study of metabolic syndrome as well as other systemic inflammatory diseases.

  Study phs003883

• Multiplexed scRNA-Seq Reveals Cellular and Genetic Correlates of SLE

  Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (160 cases, 98 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of naïve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

  Study phs002812

• Epigenomics of Neurocognitive Function in Breast Cancer

  This study harnessed the data and biospecimens from the Exercise Program in Cancer and Cognition (EPICC) study (parent study) that collected data on cognitive function, demographics, other symptoms and biospecimens at two time points (T1: enrollment, T2: six months later) within the context of a six-month randomized controlled trial of a moderate intensity aerobic exercise intervention. This study collected genome wide DNA methylation data from T1 and T2 and conducted epigenome-wide association-based analyses to find genes and biological pathways explaining variability in cognitive function and explaining how exercise mitigates cognitive decline. Our initial findings identified cg10331779 near CTNND2 (p-value=9.65×10-9) associated with processing speed and cg25906741 in MLIP (p-value=2.01×10-8) associated with subjectively measured cognitive function. Additionally, differentially methylated regions were identified near SLC6A11, PRKG1/CSTF2T, and FAM3B for processing speed and near PI4KB and SGCE/PEG10 for mental flexibility.

  Study phs003959

• High volume culture initiating in vitro evolution in neuroblastoma cell lines

  Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft systems from multiple cancer types, and in-vitro culture that certain conditions may invoke chaotic fluctuations in the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.

  Study EGAS00001007962