A single nucleotide polymorphism in the RAD51 gene modifies cancer risk in BRCA2 but not BRCA1 carriers

BRCA1 and BRCA2 carriers are at increased risk for both breast and ovarian cancer, but estimates of lifetime risk vary widely, suggesting their penetrance is modified by other genetic and/or environmental factors. The BRCA1 and BRCA2 proteins function in DNA repair in conjunction with RAD51. A preliminary report suggested that a single nucleotide polymorphism in the 5′ untranslated region of RAD51 (135C/G) increases breast cancer risk in BRCA1 and BRCA2 carriers. To investigate this effect we studied 257 female Ashkenazi Jewish carriers of one of the common BRCA1 (185delAG, 5382insC) or BRCA2 (6174delT) mutations. Of this group, 164 were affected with breast and/or ovarian cancer and 93 were unaffected. RAD51 genotyping was performed on all subjects. Among BRCA1 carriers, RAD51-135C frequency was similar in healthy and affected women [6.1% (3 of 49) and 9.9% (12 of 121), respectively], and RAD-135C did not influence age of cancer diagnosis [Hazard ratio (HR) = 1.18 for disease in RAD51-135C heterozygotes, not significant]. However, in BRCA2 carriers, RAD51-135C heterozygote frequency in affected women was 17.4% (8 of 46) compared with 4.9% (2 of 41) in unaffected women (P = 0.07). Survival analysis in BRCA2 carriers showed RAD51-135C increased risk of breast and/or ovarian cancer with an HR of 4.0 [95% confidence interval 1.6–9.8, P = 0.003]. This effect was largely due to increased breast cancer risk with an HR of 3.46 (95% confidence interval 1.3–9.2, P = 0.01) for breast cancer in BRCA2 carriers who were RAD51-135C heterozygotes. RAD51 status did not affect ovarian cancer risk. These results show RAD51-135C is a clinically significant modifier of BRCA2 penetrance, specifically in raising breast cancer risk at younger ages.

Quantitative analysis of chromosomal CGH in human breast tumors associates copy number abnormalities with p53 status and patient survival

We present a general method for rigorously identifying correlations between variations in large-scale molecular profiles and outcomes and apply it to chromosomal comparative genomic hybridization data from a set of 52 breast tumors. We identify two loci where copy number abnormalities are correlated with poor survival outcome (gain at 8q24 and loss at 9q13). We also identify a relationship between abnormalities at two loci and the mutational status of p53. Gain at 8q24 and loss at 5q15-5q21 are linked with mutant p53. The 9q and 5q losses suggest the possibility of gene products involved in breast cancer progression. The analytical techniques are general and also are applicable to the analysis of array-based expression data.