Abstract 1322: A meta-analysis of genome-wide association studies identifies novel loci that influence breast cancer prognosis
Authors: Latha Kadalayil, Sofia Khan, Heli Nevanlinna, Peter A. Fasching, Fergus J. Couch, John Hopper, Jianjun Liu, Tom Maishman, Lorraine Durcan, Carl Bloomqvist, Andy Collins, Dianna Eccles, William Tapper
Journal: Cancer Research (2017)

Abstract Familial studies were among the first to indicate that breast cancer prognosis has a heritable component. Subsequently many variants associated with prognosis have been identified using a range of techniques including genome-wide association studies (GWAs). Despite these advances, much of the heritability remains unexplained. In young women, breast cancer is characterised by a higher incidence of adverse pathological features, unique tumour gene expression profiles and worse survival. In addition, the association of risk with conventional epidemiological exposures is less clear in women with early onset. We hypothesise that some of these difference between early and late onset could be influenced by germline variation. To identify additional variants that influence breast cancer prognosis we conducted a two stage meta-analysis of four GWAs consisting of 6,042 patients from the UK (POSH), Finland (HEBCS), Germany (SUCCESS-A) and Australia (ABCFS). Cox-regression analyses were used to investigate overall survival (OS, n=1,101 events) and disease-free survival (DFS, n=1,316 events) with correction for oestrogen status (ER). These survival analyses were repeated in a subset of patients with early onset (aged ≤40 at diagnosis, n=2,315 patients, OS n=604 events, DFS n=716 events). Meta-analysis identified two intronic SNPs in ADAMTSL1 that were associated exclusively with early onset DFS, rs715212 (Pmeta=3.54x10-5) and rs10963755 (Pmeta=3.91x10-4) without heterogeneity between cohorts. Multivariable Cox-regression demonstrated that the effect of these SNPs were independent of the classical prognostic factors. Most importantly, rs715212 reached genome-wide significance (Pmultivariate=5.37x10-8) in the multivariate model. ADAMTSL1 encodes a glycoprotein that forms part of the extracellular matrix (ECM) and may function in cell-cell or cell-matrix interactions or may regulate other ADAMTS proteases. Previous studies have shown that ADAMTSL1 is hypermethylated in ER positive breast cancer tumours. Using GTEx to perform eQTL analysis, we found that rs715212 is associated with the expression of several biologically relevant genes AREG (P=0.035), TNF (P=0.015), FASLG (P=0.0031) and EGF (P=0.0018) in breast mammary tissue. Interestingly, separate studies have shown that AREG is overexpressed in ER-positive breast tumours from pre-menopausal women versus post-menopausal women. Furthermore, AREG is differentially expressed between parous and non-parous mammary glands and is persistently downregulated by parity, which suggests it may contribute to the susceptibility of the nulliparous gland to breast cancer. We conclude that rs715212 is associated with an increased risk of disease progression in patients with early onset and speculate that this could be due to an interaction with the expression of AREG. Note: This abstract was not presented at the meeting. Citation Format: Latha Kadalayil, Sofia Khan, Heli Nevanlinna, Peter A. Fasching, Fergus J. Couch, John Hopper, Jianjun Liu, Tom Maishman, Lorraine Durcan, Carl Bloomqvist, Andy Collins, Dianna Eccles, William Tapper. A meta-analysis of genome-wide association studies identifies novel loci that influence breast cancer prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1322. doi:10.1158/1538-7445.AM2017-1322