3955 results for "*geneti*"

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• Genomic Data Archive From the Network for Pancreatic Organ Donors With Diabetes

  The Network for Pancreatic Organ Donors with Diabetes (nPOD) is the largest biorepository of human pancreata from organ donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, and islet autoantibody positive (AAb+)/pre-T1D. The mission of the nPOD is to distribute biospecimens and associated de-identified data/metadata to an international researcher network, and to promote the development of new treatments for these diabetes conditions. Here, we describe the release of high-parameter genotyping data for the nPOD cohort. Specifically, 372 subjects were genotyped using a customized precision medicine single nucleotide polymorphism (SNP) microarray (UFDIchip). These data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 subjects were queried for rare known and novel coding region variants via whole exome sequencing (WES). These data are now publicly available, enabling genotype-selected sample requests and the study of novel genotype : phenotype associations, ultimately to explain diabetes heterogeneity and inform precision medicine strategies to interrupt diabetes pathogenesis.

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• Oncogenomics of Malignant Peripheral Nerve Sheath Tumors

  Malignant peripheral nerve sheath tumors (MPNSTs) are a group of highly aggressive soft tissue sarcomas that may occur sporadically, in association with neurofibromatosis type I (NF1-associated), or after radiotherapy (RT-associated). We utilized comprehensive genomic approaches and identified recurrent loss-of-function somatic alterations in the Polycomb repressive complex 2 (PRC2) core components EED or SUZ12. Genetic loss of either of these two genes results in complete loss of H3K27me3 and aberrant transcriptional programming in the affected tumors.

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• Predictive impact of rare genomic copy number variations in siblings of individuals with autism spectrum disorders

  Identification of genetic biomarkers associated with autism spectrum disorders (ASDs) could improve recurrence prediction for families with a child with ASD. Here, we describe clinical microarray findings for 253 longitudinally phenotyped ASD families from the Baby Siblings Research Consortium (BSRC), encompassing 288 infant siblings. By age 3, 103 siblings (35.8%) were diagnosed with ASD and 54 (18.8%) were developing atypically. Thirteen siblings have copy number variants (CNVs) involving ASD-relevant genes: 6 with ASD, 5 atypically developing, and 2 typically developing. Within these families, an ASD-related CNV in a sibling has a positive predictive value (PPV) for ASD or atypical development of 0.83; the Simons Simplex Collection of ASD families shows similar PPVs. Polygenic risk analyses suggest that common genetic variants may also contribute to ASD. CNV findings would have been pre-symptomatically predictive of ASD or atypical development in 11 (7%) of the 157 BSRC siblings who were eventually diagnosed clinically.

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• Integrated Genomic Analyses of Cutaneous T Cell Lymphomas Reveal the Molecular Bases for Disease Heterogeneity

  Cutaneous T cell lymphomas (CTCLs) are a clinically diverse collection of lymphomas of the skin-homing T cell. In the present study, we performed DNA and RNA sequencing on a cohort of CTCLs with representative samples from varying disease subtypes and stages. We characterized the landscape of putative driver genes, identified genetic relationships between CTCLs across disease stages, and inferred molecular subtypes in patients with stage-matched leukemic disease. Collectively, our findings clarify CTCL genetics and provide novel insights into pathways that drive diverse disease phenotypes. DNA and RNA sequencing was performed on 114 and 96 samples respectively. Tumor samples were obtained from University of Chicago (Chicago, IL), Northwestern University (Chicago, IL) and Yale University (New Haven, CT). 

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• Genomic Characterization of Meningiomas

  Meningiomas are the most common primary brain tumor in the US. Although the tumor suppressor gene NF2 is disrupted in approximately half of meningiomas, the complete spectrum of genetic changes in meningiomas remains poorly understood, particularly in the large subset of tumors without NF2 alterations. Therefore we performed whole-genome sequencing from 11 Grade I meningioma tumor-normal pairs and whole-exome sequencing from an additional 6 tumor-normal pairs to identify somatic mutations, insertions-deletions, copy-number alterations and rearrangements. We validated our results by performing focused sequencing across 48 additional meningiomas.

  Study phs000552

• DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

  Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

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• Genetic Determinants of Viral Clearance in HCV-Infected Populations

  The World Health Organization estimates there are 170 million persons with HCV infection worldwide, and an estimated 4 million persons are infected in the United States. Persistent HCV infection can cause cirrhosis and hepatocellular cancer. Long term disease consequences do not occur in persons who spontaneously recover. It is not known why 10-40% recover from hepatitis C (and are not at increased risk of cirrhosis and cancer), but that knowledge would contribute to efforts to treat and/or prevent HCV infection. The overall purpose of this study is to investigate the host genetic basis for recovery from hepatitis C virus (HCV) infection. There is strong evidence that host genetic differences determine HCV recovery. After accidental exposure to the same HCV inoculum, some persons recover while others develop persistent infection. Recovery from HCV infection is an outstanding phenotype for genetic studies since both viral exposure and viral recovery can be ascertained with high sensitivity and specificity and since there are no known viral or environmental determinants. The study group is comprised of an ethnically and geographically diverse international population. All cohorts comprising this study group of 3350 individuals are well characterized. This case-control study is comprised of approximately 40% clearance individuals who are matched by age and HIV status within their respective cohorts at a ratio of 1:1 or 1:2 with HCV chronically infected individuals.

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• National Cancer Institute (NCI) Study of Lung Cancer and Smoking Phenotypes in African-American Cases and Controls

  This is a two-stage case-control study designed to evaluate the association between common genetic variants and the risk of lung cancer. The stage 1 studies included 1737 cases and 3602 controls from the following studies: MD Anderson Lung Cancer Epidemiology Study, The Multiethnic Cohort Study (MEC), NCI-MD Lung Cancer-Case Control Study, Northern California Lung Cancer Study, Project CHURCH (Creating a Higher Understanding of Cancer Research δ Community Health), Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), Southern Community Cohort Study (SCCS), and the Karmanos Cancer Institute at Wayne State University (KCI/WSU). The stage 2 studies included an independent set of 866 cases and 796 controls from the following studies: The Black Women's Health Study (BWHS), The Harvard-MGH Lung Cancer Susceptibility Study (HLCS), MD Anderson Lung Cancer Epidemiology Study, MD Anderson/LBJ Hospital Biorepository, NCI-MD Lung Cancer Case-Control Study, Northern California Lung Cancer Study, Philadelphia Lung Cancer Study on Gene Environment Interactions (Plus-Gene), Southern Community Cohort Study (SCCS), and KCI/WSU.

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• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

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• A National Translational Science Network of Precision-Based Immunotherapy for Primary Liver Cancer (PLC)

  The primary objective of the NCI-CLARITY study is to establish a biospecimen repository for genomic, genetic and epigenetic analysis to study the biology of primary liver cancer (PLC) development and progression. Secondary objectives include predicting overall and progression-free survival following immunotherapy. In the retrospective phase, anonymous archival tissue from PLC patients was obtained from five participating sites. Whole exome and transcriptome sequencing was generated and used to predict overall survival in response to immunotherapy.

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