A genetic-based approach to personalized prostate cancer screening and treatment. Issue 1 (January 2015)

• Record Type: Journal Article
• Authors: Helfand, Brian T.; Catalona, William J.; Xu, Jianfeng
• Is Part Of: Current opinion in urology. Volume 25:Issue 1(2015:Jan.)
• Publication Date: 2015-01
• Subjects: Urology -- Periodicals; Review Literature -- Bibliography; Review Literature -- Periodicals; Male Urogenital Diseases -- Bibliography; Male Urogenital Diseases -- Periodicals; Female Urogenital Diseases -- Bibliography; Female Urogenital Diseases -- Periodicals; Urologic Diseases -- Bibliography; Urologic Diseases -- Periodicals; Periodicals; 616.6005
• DOI: 10.1097/MOU.0000000000000130
• Languages: English
• ISSNs: 1473-6586

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <sec> <title>Purpose of review</title> <p>Recent advances in sequencing technologies have allowed for the identification of genetic variants within germline DNA that can explain a significant portion of the genetic underpinnings of prostate cancer. Despite evidence suggesting that these genetic variants can be used for improved risk stratification, they have not yet been routinely incorporated into routine clinical practice. This review highlights their potential utility in prostate cancer screening.</p> </sec> <sec> <title>Recent findings</title> <p>There are now almost 100 genetic variants, called single nucleotide polymorphisms (SNPs) that have been recently found to be associated with the risk of developing prostate cancer. In addition, some of these prostate cancer risk SNPs have also been found to influence prostate specific antigen (PSA) expression levels and potentially aggressive disease.</p> </sec> <sec> <title>Summary</title> <p>Incorporation of panels of prostate cancer risk SNPs into clinical practice offers potential to provide improvements in patient selection for prostate cancer screening; PSA interpretation (e.g. by correcting for the presence of SNPs that influence PSA expression levels; decision for biopsy (using prostate cancer risk SNPs); and possibly the decision for treatment. A proposed clinical algorithm incorporating these prostate cancer risk SNPs is discussed.</p> </sec> </abstract>