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• Action to Control Cardiovascular Risk in Diabetes (ACCORD) Clinical Trial

  The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial was a randomized, multicenter, double 2 x 2 factorial design study involving 10,251 middle-aged and older participants with type-2 diabetes who are at high risk for CVD events because of existing CVD or additional risk factors. The purpose of ACCORD was to determine if intensive glycemic control, intensive lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. The ACCORD trial failed to show a beneficial effect of intensive blood pressure or lipid therapy on the primary outcome, and intensive glycemia management actually increased mortality. The hypothesis underlying this ancillary study is that the failure of ACCORD to achieve its goal of reducing cardiovascular risk in diabetic patients through intensive management of hyperglycemia, dyslipidemia, and hypertension may be the result of variation in drug response due to genetic variation between individual participants. Benefits of intensive therapy may accrue to subsets of subjects with specific genetic variants predisposing to efficacious responses to particular therapeutic regimens, and harms may accrue to those with other variants predisposing to poor efficacy or adverse events. Identifying these variants could lead to a precision medicine approach to treating diabetes where each patient's genetic profile could identify the most efficacious treatment regimen with the lowest likelihood of adverse events. To test this hypothesis, a genome-wide genetic analysis was undertaken, incorporating both common variants distributed across the genome and rare variants targeted to exonic regions. Associations of genetic variants with short term responses to individual medicines as well as long term outcomes were investigated. The dataset is composed of genetic data from the ~6100 participants who agreed to participate in the ACCORD optional genetic studies and who allowed broad investigator access to their samples and the data derived from those samples, and from whom a DNA sample of sufficient quality was obtained. While a total of 8514 participants consented to the optional genetics studies, not all consented to broad investigator access, and those who did not are not included in this dataset, although they were also genotyped. Access to these additional genotypes can only be obtained by direct collaboration with the investigators of this study. Phenotype data used in the association analyses are derived from the ACCORD public release clinical data set, which has been made available through BioLINCC.

  Study phs001411

• NHLBI GO-ESP: Family Studies (Thoracic aortic aneurysms leading to acute aortic dissections)

  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. Acute aortic dissections are a common cause of premature death in the United States, ranking as high as the 15th leading cause of death. The goal of the Familial Thoracic Aortic Aneurysm and Dissection (TAAD) study at the University of Texas Health Science Center at Houston is to identify the genes causing thoracic aortic disease, and prevent premature deaths due to aortic dissections by identifying individuals who are genetically predisposed to the disease and initiating medical and surgical therapies to prevent dissections. In this study ("NHLBI GO-ESP Family Studies: Aortic Disease"), we have selected a series of families from the TAAD study, and are performing exome sequencing of 2 to 3 individuals per family.

  Study phs000347

• Genomic and Genetic Characterization of Prostate Tumors Treated with Neoadjuvant Intense Androgen Deprivation Therapy

  The purpose of this study was to develop better ways of detecting prostate cancer before and after pre-operative treatment, and to test the feasibility of multi parametric magnetic resonance imaging (mpMRI) for the localization and detection of focal prostate cancer both before and after pre-operative treatment with ADT and enzalutamide. In this study, patients with intermediate and high risk prostate cancer received six months of neoadjuvant intense androgen deprivation therapy prior to radical prostatectomy. Biopsies were acquired prior to treatment. Tissue from biopsy and radical prostatectomy were subjected to sequencing and analysis for determination of features associated with response or resistance to treatment.

  Study phs001938

• Genomics of Relapsed Small Cell Lung Cancer Progression

  Small cell lung cancer (SCLC) accounts for nearly 15% of all patients with lung cancer. Though the response to initial therapy is favorable in many patients, a majority of patients go on to develop recurrent disease which is very difficult to treat. The response rates to chemotherapy are very low and most patients succumb to relapsed SCLC within a few months. Virtually no progress has been made in the treatment of SCLC in the last three decades. In order to better understand the molecular alterations in relapsed SCLC, we have generated exome and RNA sequence from normal, primary tumor and relapse tissues of SCLC patients.

  Study phs001049

• Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

  Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

  Study JGAS000108

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002509

• Combination Therapies for Personalised Cancer Medicine in 11-18

  This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002579

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• CTN - 0051: Extended-Release Naltrexone vs. Buprenorphine for Opioid Treatment (X:BOT)

  The overarching goal of CTN-0051 is to foster adoption of new relapse-prevention pharmacotherapies in community-based treatment programs (CTPs) where these could have a substantial public health impact. To this end CTN-0051 will assess the comparative effectiveness of extended-release injectable naltrexone (XR-NTX, Vivitrol®), an opioid antagonist recently approved and indicated for the prevention of relapse to opioid dependence, versus buprenorphine-naloxone (BUP-NX, Suboxone®), a high affinity partial agonist indicated for maintenance treatment of opioid dependence, as pharmacotherapeutic aids to recovery. The study is conducted in 8 CTN-affiliated CTPs that provide or partner with detoxification services (inpatient/residential) which have the capacity to maintain participants opioid-free for approximately 3-7 days, have the capacity to provide medication-assisted therapy, and can provide a minimum of one group or individual counseling session per week during the 24-week treatment period. Up to 600 eligible participants will be randomized to treatment with XR-NTX or BUP-NX for 24 weeks (sufficient to include 350 participants who are randomized more than 72 hours after their last opioid). To maximize generalizability, the point of randomization is flexible, from shortly after program admission until just prior to program discharge. The primary goal of the study is to estimate the difference, if one exists, between XR-NTX and BUP-NX in the distribution of the time to relapse (i.e., loss of persistent abstinence) during the 6-month trial. The primary outcome measure is the time to the event, with the event called relapse. Secondary objectives are to: (1) compare outcome on XR-NTX versus BUP-NX across a range of clinical safety and secondary efficacy domains, (2) explore demographic, clinical, and genetic predictors of successful treatment and moderators of differential effectiveness (i.e., what variables may help clinicians choose which of these treatments is best for a given patient), and (3) collect a limited dataset to permit analyses of economic costs and benefits of the two treatments.

  Study phs002876