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PARK2, a gene associated with Parkinson disease, is a tumor suppressor in human malignancies. Here, we show that c.823C>T (p.Arg275Trp), a germline mutation in PARK2, is present in a family with eight cases of lung cancer. The resulting amino acid change, p.Arg275Trp, is located in the highly conserved RING finger 1 domain of PARK2, which encodes an E3 ubiquitin ligase. Upon further analysis, the c.823C>T mutation was detected in three additional families affected by lung cancer. The effect size for PARK2 c.823C>T (odds ratio = 5.24) in white individuals was larger than those reported for variants from lung cancer genome-wide association studies. These data implicate this PARK2 germline mutation as a genetic susceptibility factor for lung cancer. Our results provide a rationale for further investigations of this specific mutation and gene for evaluation of the possibility of developing targeted therapies against lung cancer in individuals with PARK2 variants by compensating for the loss-of-function effect caused by the associated variation.
Pubmed ID: 25640678 RIS Download
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Functional genomics data repository supporting MIAME-compliant data submissions. Includes microarray-based experiments measuring the abundance of mRNA, genomic DNA, and protein molecules, as well as non-array-based technologies such as serial analysis of gene expression (SAGE) and mass spectrometry proteomic technology. Array- and sequence-based data are accepted. Collection of curated gene expression DataSets, as well as original Series and Platform records. The database can be searched using keywords, organism, DataSet type and authors. DataSet records contain additional resources including cluster tools and differential expression queries.
View all literature mentionsDatabase for genomes that have been completely sequenced, have active research community to contribute gene-specific information, or that are scheduled for intense sequence analysis. Includes nomenclature, map location, gene products and their attributes, markers, phenotypes, and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases. All entries follow NCBI's format for data collections. Content of Entrez Gene represents result of curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases, and from many other databases available from NCBI. Records are assigned unique, stable and tracked integers as identifiers. Content is updated as new information becomes available.
View all literature mentionsProject exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).
View all literature mentionsCollection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. An aggregated data platform for genome sequencing data created by a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 61,486 unrelated individuals sequenced as part of various disease-specific and population genetic studies. They have removed individuals affected by severe pediatric disease, so this data set should serve as a useful reference set of allele frequencies for severe disease studies. All of the raw data from these projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects. They ask that you not publish global (genome-wide) analyses of these data until after the ExAC flagship paper has been published, estimated to be in early 2015. If you''re uncertain which category your analyses fall into, please email them. The aggregation and release of summary data from the exomes collected by the Exome Aggregation Consortium has been approved by the Partners IRB (protocol 2013P001477, Genomic approaches to gene discovery in rare neuromuscular diseases).
View all literature mentionsOnline catalog of human genes and genetic disorders, for clinical features, phenotypes and genes. Collection of human genes and genetic phenotypes, focusing on relationship between phenotype and genotype. Referenced overviews in OMIM contain information on all known mendelian disorders and variety of related genes. It is updated daily, and entries contain copious links to other genetics resources.
View all literature mentionsThe goal of the project is to discover novel genes and mechanisms contributing to heart, lung and blood disorders by pioneering the application of next-generation sequencing of the protein coding regions of the human genome across diverse, richly-phenotyped populations and to share these datasets and findings with the scientific community to extend and enrich the diagnosis, management and treatment of heart, lung and blood disorders. The groups participating and collaborating in the NHLBI GO ESP include: Seattle GO - University of Washington, Seattle, WA Broad GO - Broad Institute of MIT and Harvard, Cambridge, MA WHISP GO - Ohio State University Medical Center, Columbus, OH Lung GO - University of Washington, Seattle, WA WashU GO - Washington University, St. Louis, MO Heart GO - University of Virginia Health System, Charlottesville, VA ChargeS GO - University of Texas Health Sciences Center at Houston
View all literature mentionsAn efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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