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Single nucleotide polymorphisms (SNPs) in DNA glycosylase genes involved in the base excision repair (BER) pathway can modify breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We previously found that SNP rs34259 in the uracil-DNA glycosylase gene (UNG) might decrease ovarian cancer risk in BRCA2 mutation carriers. In the present study, we validated this finding in a larger series of familial breast and ovarian cancer patients to gain insights into how this UNG variant exerts its protective effect. We found that rs34259 is associated with significant UNG downregulation and with lower levels of DNA damage at telomeres. In addition, we found that this SNP is associated with significantly lower oxidative stress susceptibility and lower uracil accumulation at telomeres in BRCA2 mutation carriers. Our findings help to explain the association of this variant with a lower cancer risk in BRCA2 mutation carriers and highlight the importance of genetic changes in BER pathway genes as modifiers of cancer susceptibility for BRCA1 and BRCA2 mutation carriers.
Pubmed ID: 30747491
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A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.
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