Mutational landscape of candidate genes in familial prostate cancer.

Journal Article (Journal Article)

BACKGROUND: Family history is a major risk factor for prostate cancer (PCa), suggesting a genetic component to the disease. However, traditional linkage and association studies have failed to fully elucidate the underlying genetic basis of familial PCa. METHODS: Here, we use a candidate gene approach to identify potential PCa susceptibility variants in whole exome sequencing data from familial PCa cases. Six hundred ninety-seven candidate genes were identified based on function, location near a known chromosome 17 linkage signal, and/or previous association with prostate or other cancers. Single nucleotide variants (SNVs) in these candidate genes were identified in whole exome sequence data from 33 PCa cases from 11 multiplex PCa families (3 cases/family). RESULTS: Overall, 4,856 candidate gene SNVs were identified, including 1,052 missense and 10 nonsense variants. Twenty missense variants were shared by all three family members in each family in which they were observed. Additionally, 15 missense variants were shared by two of three family members and predicted to be deleterious by five different algorithms. Four missense variants, BLM Gln123Arg, PARP2 Arg283Gln, LRCC46 Ala295Thr and KIF2B Pro91Leu, and one nonsense variant, CYP3A43 Arg441Ter, showed complete co-segregation with PCa status. Twelve additional variants displayed partial co-segregation with PCa. CONCLUSIONS: Forty-three nonsense and shared, missense variants were identified in our candidate genes. Further research is needed to determine the contribution of these variants to PCa susceptibility.

Full Text

Duke Authors

Cited Authors

  • Johnson, AM; Zuhlke, KA; Plotts, C; McDonnell, SK; Middha, S; Riska, SM; Schaid, DJ; Thibodeau, SN; Douglas, JA; Cooney, KA

Published Date

  • October 2014

Published In

Volume / Issue

  • 74 / 14

Start / End Page

  • 1371 - 1378

PubMed ID

  • 25111073

Pubmed Central ID

  • PMC4142071

Electronic International Standard Serial Number (EISSN)

  • 1097-0045

Digital Object Identifier (DOI)

  • 10.1002/pros.22849


  • eng

Conference Location

  • United States