Novel predictors of breast cancer survival derived from miRNA activity analysis

Purpose: Breast cancer is among the leading causes of cancer death; discovery of novel prognostic markers is needed to improve outcomes. Combining systems biology and epidemiology, we investigated microRNA-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 microRNAs "activities" which were predictive of breast cancer mortality in published databases. We profiled microRNA-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 hazard ratios (HR) 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 microRNA 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], while 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 PAM-50 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.

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