Prognostic value of NDRG1 and SPARC protein expression in breast cancer patients.

An increasing number of studies have shown altered expression of secreted protein acidic and rich in cysteine (SPARC) and N-myc down-regulated gene (NDRG1) in several malignancies, including breast carcinoma; however, the role of these potential biomarkers in tumor development and progression is controversial. In this study, NDRG1 and SPARC protein expression was evaluated by immunohistochemistry on tissue microarrays containing breast tumor specimens from patients with 10 years of follow-up. NDRG1 and SPARC protein expression was determined in 596 patients along with other prognostic markers, such as ER, PR, and HER2. The status of NDRG1 and SPARC protein expression was correlated with prognostic variables and patient clinical outcome. Immunostaining revealed that 272 of the 596 cases (45.6%) were positive for NDRG1 and 431 (72.3%) were positive for SPARC. Statistically significant differences were found between the presence of SPARC and NDRG1 protein expression and standard clinicopathological variables. Kaplan-Meier analysis showed that NDRG1 positivity was directly associated with shorter disease-free survival (DFS, P < 0.001) and overall survival (OS, P < 0.001). In contrast, patients expressing low levels of SPARC protein had worse DFS (P = 0.001) and OS (P = 0.001) compared to those expressing high levels. Combined analysis of the two markers indicated that DFS (P < 0.001) and OS rates (P < 0.001) were lowest for patients with NDRG1-positive and SPARC-negative tumors. Furthermore, NDRG1 over-expression and SPARC down-regulation correlated with poor prognosis in patients with luminal A or triple-negative subtype breast cancer. On multivariate analysis using a Cox proportional hazards model, NDRG1 and SPARC protein expression were independent prognostic factors for both DFS and OS of breast cancer patients. These data indicate that NDRG1 over-expression and SPARC down-regulation could play important roles in breast cancer progression and serve as useful biomarkers to better define breast cancer prognosis.