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. 2017 Nov 21;8(1):1632.
doi: 10.1038/s41467-017-01775-y.

Germline Variation in ADAMTSL1 Is Associated With Prognosis Following Breast Cancer Treatment in Young Women

Free PMC article

Germline Variation in ADAMTSL1 Is Associated With Prognosis Following Breast Cancer Treatment in Young Women

Latha Kadalayil et al. Nat Commun. .
Free PMC article


To identify genetic variants associated with breast cancer prognosis we conduct a meta-analysis of overall survival (OS) and disease-free survival (DFS) in 6042 patients from four cohorts. In young women, breast cancer is characterized by a higher incidence of adverse pathological features, unique gene expression profiles and worse survival, which may relate to germline variation. To explore this hypothesis, we also perform survival analysis in 2315 patients aged ≤ 40 years at diagnosis. Here, we identify two SNPs associated with early-onset DFS, rs715212 (P meta = 3.54 × 10-5) and rs10963755 (P meta = 3.91 × 10-4) in ADAMTSL1. The effect of these SNPs is independent of classical prognostic factors and there is no heterogeneity between cohorts. Most importantly, the association with rs715212 is noteworthy (FPRP <0.2) and approaches genome-wide significance in multivariable analysis (P multivariable = 5.37 × 10-8). Expression quantitative trait analysis provides tentative evidence that rs715212 may influence AREG expression (P eQTL = 0.035), although further functional studies are needed to confirm this association and determine a mechanism.

Conflict of interest statement

The authors declare no competing financial interests.


Fig. 1
Fig. 1
Genome-wide analysis of breast cancer survival. The Manhattan plot shows the result of the stage-1 meta-analysis. Results are plotted as –log10 of the P-value from Cox regression. For each SNP the most significant P-value is selected from the analysis of either overall survival (OS) or disease-free survival (DFS) in all patients or the subset with early onset. The four most significant SNPs after meta-analysis of stages 1 and 2 are highlighted in green (rs410155 and rs12302097 associated with OS and DFS respectively in the whole cohort and rs715212 and rs10963755 associated with DFS in patients with early onset). This plot was produced using the qqman R package
Fig. 2
Fig. 2
Forest plot and meta-analysis for the four most significant SNPs associated with overall survival (OS) or disease-free survival (DFS). Forest plot showing the event rate, hazard ratio (HR), 95% confidence interval (CI) and significance level (P-value) from Cox regression in each cohort and the combined analysis for the most significant SNPs associated with DFS and OS. ABCFS*: evidence for association with OS in the ABCFS cohort is shown for each SNP but these results are excluded from the meta-analyses of DFS. The SNP subtotal rows show the result for a fixed effects meta-analysis across four studies for rs715212, rs10963755 and rs12302097 and five studies for rs410155 using I 2 and Cochran Q-statistic to assess heterogeneity in effect sizes between cohorts
Fig. 3
Fig. 3
Kaplan–Meir survival plots for the four most significant SNPs identified by meta-analyses. Kaplan–Meier plots from univariate analysis of the most significant SNP associated with disease-free survival (DFS) in cases with early onset (a, rs715212 and b, rs10963755), DFS in all cases (c, rs12302097) and overall survival (OS) in all cases (d, rs410155). For OS, the data from all five cohorts (ABCFS, HEBCS, POSH stages 1 and 2 and SUCCESS-A) was pooled whereas for DFS data were pooled across four cohorts because DFS was not recorded in the ABCFS cohort. HR: hazard ratio with 95% confidence interval
Fig. 4
Fig. 4
Regional plots of association with survival (OS or DFS) at stage-1 meta-analysis, recombination rate and gene context for the most significant SNPs. Results from the stage-1 meta-analyses in a region surrounding the most significant SNP associated with DFS in patients with early onset (a, rs715212 and rs10963755), DFS in all patients (b, rs12302097) and OS in all patients (c, rs410155). In each plot, a purple diamond identifies the index SNP and the colour of other SNPs represent their linkage disequilibrium (r 2) with the index SNP from light blue (r 2 ≤ 0.4) to red (r 2 ≥ 0.8). The middle panel displays the 15 state chromatin segmentation track (ChromHMM) in breast variant human mammary epithelial cells (vHMECs, E028), mammary epithelial primary cells (HMECs, E119) and breast myoepithelial primary cells (E027) using data from the HapMap ENCODE Project. The lower panels show genes and their direction of transcription (arrows). Physical positions are relative to build 37 (hg19) of the human genome

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