Association of breast cancer risk loci with breast cancer survival.

Author(s): Barrdahl M,  Canzian F,  Lindström S,  Shui I,  Black A,  Hoover RN,  Ziegler RG,  Buring JE,  Chanock SJ,  Diver WR,  Gapstur SM,  Gaudet MM,  Giles GG,  Haiman C,  Henderson BE,  Hankinson S,  Hunter DJ,  Joshi AD,  Kraft P,  Lee IM,  Le Marchand L,  Milne RL,  Southey MC,  Willett W,  Gunter M,  Panico S,  Sund M,  Weiderpass E,  Sánchez MJ,  Overvad K,  Dossus L,  Peeters PH,  Khaw KT,  Trichopoulos D,  Kaaks R,  Campa D

Journal: Int J Cancer

Date: 2015 Dec 15

Major Program(s) or Research Group(s): PLCO

PubMed ID: 25611573

PMC ID: PMC4615576

Abstract: The survival of breast cancer patients is largely influenced by tumor characteristics, such as TNM stage, tumor grade and hormone receptor status. However, there is growing evidence that inherited genetic variation might affect the disease prognosis and response to treatment. Several lines of evidence suggest that alleles influencing breast cancer risk might also be associated with breast cancer survival. We examined the associations between 35 breast cancer susceptibility loci and the disease over-all survival (OS) in 10,255 breast cancer patients from the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3) of which 1,379 died, including 754 of breast cancer. We also conducted a meta-analysis of almost 35,000 patients and 5,000 deaths, combining results from BPC3 and the Breast Cancer Association Consortium (BCAC) and performed in silico analyses of SNPs with significant associations. In BPC3, the C allele of LSP1-rs3817198 was significantly associated with improved OS (HRper-allele =0.70; 95% CI: 0.58-0.85; ptrend  = 2.84 × 10(-4) ; HRheterozygotes  = 0.71; 95% CI: 0.55-0.92; HRhomozygotes  = 0.48; 95% CI: 0.31-0.76; p2DF  = 1.45 × 10(-3) ). In silico, the C allele of LSP1-rs3817198 was predicted to increase expression of the tumor suppressor cyclin-dependent kinase inhibitor 1C (CDKN1C). In the meta-analysis, TNRC9-rs3803662 was significantly associated with increased death hazard (HRMETA =1.09; 95% CI: 1.04-1.15; ptrend  = 6.6 × 10(-4) ; HRheterozygotes  = 0.96 95% CI: 0.90-1.03; HRhomozygotes  = 1.21; 95% CI: 1.09-1.35; p2DF =1.25 × 10(-4) ). In conclusion, we show that there is little overlap between the breast cancer risk single nucleotide polymorphisms (SNPs) identified so far and the SNPs associated with breast cancer prognosis, with the possible exceptions of LSP1-rs3817198 and TNRC9-rs3803662.