Abstract 4794: Identification of FOXM1 driven gene network as a prognostic marker in breast cancer

Abstract

Abstract A transcription factor FOXM1 is known to play a key role in cell cycle progression where endogenous FOXM1 expression peaks at S and G2/M phases. It was previously reported that expression level of FOXM1 in breast cancer was strongly correlated with patient survival, since FOXM1 influenced endocrine therapy and chemo-response effect. The aim of this study is to estimate prognostic value of FOXM1 gene and to identify novel markers interconnected with FOXM1 to predict heterogeneous breast cancer behaviors. Microarray gene expression profiling was performed using gene expression data obtained from 317 Korean patients with breast cancer to identify a signature associated with FOXM1. Various statistical methods, including the leave-one-out cross validation, were applied to identify a gene expression signature able to predict breast cancer outcome. The predictive value of the signature was verified in the two larger independent cohorts obtained from a public database. Unsupervised cluster analysis of gene expression data from the Korean cohort showed highly concordant subtypes of Caucasian cohort. Significant differences in overall and disease specific survival between the subgroups divided by the expression signature of FOXM1-associated genes were observed (log-rank test, each P <0.001, respectively). Multivariate Cox regression analysis revealed that the expression signature of FOXM1-associated genes was a strong predictor of breast cancer outcomes. Our findings were verified in the two independent patient cohorts and confirmed that the signature produced consistent prediction patterns. Finally, gene network analyses in the signature revealed that, FOXO1, CCNK, MYC, BRD4 and EIF4G1 could be important mediators interconnected with FOXM1 in the breast cancer behavior. The expression signature of FOXM1 and its associated genes represents a promising diagnostic tool for the identification of breast cancer patients that have a high risk of poor clinical behavior. Note: This abstract was not presented at the meeting. Citation Format: In-Sun Chu, Seon-Kyu Kim, Yun-Gil Roh, Sun-Hee Leem. Identification of FOXM1 driven gene network as a prognostic marker in breast cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4794. doi:10.1158/1538-7445.AM2015-4794