Fig. S2. Function of false-positives (red line), false-negatives (green line) and sum of false-positives and false-negatives (blue line), depending on the cut-off value of gene expression levels. Horizontal line indicates the cut-off chosen as giving the minimal sum of false-positives and false-negatives.
ARTICLE ABSTRACTPurpose: Breast cancer is among the leading causes of cancer-related death; discovery of novel prognostic markers is needed to improve outcomes. Combining systems biology and epidemiology, we investigated miRNA-associated genes and breast cancer survival in a well-characterized population-based study.Experimental Design: A recently developed algorithm, ActMiR, was used to identify key miRNA “activities” corresponding to target gene degradation, which were predictive of breast cancer mortality in published databases. We profiled miRNA-associated genes in tumors from our well-characterized population-based cohort of 606 women with first primary breast cancer. Cox proportional hazards models were used to estimate HRs and 95% confidence intervals (CI), after 15+ years of follow-up with 119 breast cancer–specific deaths.Results: miR-500a activity was identified as a key miRNA for estrogen receptor–positive breast cancer mortality using public databases. From a panel of 161 miR-500a–associated genes profiled, 73 were significantly associated with breast cancer–specific mortality (FDR < 0.05) in our population, among which two clusters were observed to have opposing directions of association. For example, high level of SUSD3 was associated with reduced breast cancer–specific mortality (HR = 0.3; 95% CI, 0.2–0.4), whereas the opposite was observed for TPX2 (HR = 2.7; 95% CI, 1.8–3.9). Most importantly, we identified set of genes for which associations with breast cancer–specific mortality were independent of known prognostic factors, including hormone receptor status and PAM50–derived risk-of-recurrence scores. These results are validated in independent datasets.Conclusions: We identified novel markers that may improve prognostic efficiency while shedding light on molecular mechanisms of breast cancer progression. Clin Cancer Res; 24(3); 581–91. ©2017 AACR.