Journal
CANCER RESEARCH
Volume 71, Issue 21, Pages 6728-6737Publisher
AMER ASSOC CANCER RESEARCH
DOI: 10.1158/0008-5472.CAN-11-1870
Keywords
-
Categories
Funding
- [R37 DK42412]
- [R01DK071892]
Ask authors/readers for more resources
Changes in iron regulation characterize the malignant state. However, the pathways that effect these changes and their specific impact on prognosis remain poorly understood. We capitalized on publicly available microarray datasets comprising 674 breast cancer cases to systematically investigate how expression of genes related to iron metabolism is linked to breast cancer prognosis. Of 61 genes involved in iron regulation, 49% were statistically significantly associated with distant metastasis-free survival. Cases were divided into test and training cohorts, and the supervised principal component method was used to stratify cases into risk groups. Optimal risk stratification was achieved with a model comprising 16 genes, which we term the iron regulatory gene signature (IRGS). Multivariable analysis revealed that the IRGS contributes information not captured by conventional prognostic indicators (HR = 1.61; 95% confidence interval: 1.16-2.24; P = 0.004). The IRGS successfully stratified homogeneously treated patients, including ER+ patients treated with tamoxifen monotherapy, both with (P = 0.006) and without (P = 0.03) lymph node metastases. To test whether multiple pathways were embedded within the IRGS, we evaluated the performance of two gene dyads with known roles in iron biology in ER+ patients treated with tamoxifen monotherapy (n = 371). For both dyads, gene combinations that minimized intracellular iron content [anti-import: TFRCLow/HFEHigh; or pro-export: SLC40A1 (ferroportin) (High)/HAMP(Low)] were associated with favorable prognosis (P < 0.005). Although the clinical utility of the IRGS will require further evaluation, its ability to both identify high-risk patients within traditionally low-risk groups and low-risk patients within high-risk groups has the potential to affect therapeutic decision making. Cancer Res; 71(21); 6728-37. (C)2011 AACR.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available