Table S3 (Excel file). Association of profiled genes with breast cancer mortality among participants in the LIBCSP, in different subsets or adjustments. For all analyses, age and tumor stage were included as cofactors; "ERPR_all" - included all patients; "ERPR_pos" - ER|PR+ patients; "ERPR_neg" - ER-/PR- patients; "ERPR_adj" - all patients, with ER/PR status as additional cofactor; "ROR_adj" - all patients, with ROR group as additional cofactor; "ROR_high" - patients assigned to high ROR group; "ROR_low+med" - patients assigned to low and medium ROR groups. For each analysis, columns are as follows: HR - hazard ratio; HR.CI - 95% confidence interval for HR; p - unadjusted p-value; p.BH - Benjamini-Hochberg-adjusted p-value; q - decile threshold for high/low expression level stratification; N.hi - number of patients in "high expression" group.
ARTICLE ABSTRACT
Purpose: 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.
