Abstract 4436: Novel microRNA signature score to predict bone metastasis and prognosis of breast cancer

Abstract

Abstract Backgrounds: 40,000 US women still die with breast cancer every year. Vast majority of death occur after they develop metastasis, where bone is the most frequent site for breast cancer. New measures to identify the patients who develop metastasis allow us to intervene early, which is expected to prolong survival. The aim of this study is to establish a microRNA (miRNA) signature scoring system that can predict bone metastasis and survival utilizing integrated transcriptomics analyses in breast cancer. Materials and Methods: Both clinical and RNA expression data, including microRNA and mRNA, of 1051 patients were retrieved from The Cancer Genome Atlas (TCGA). 1) Multivariate Cox proportional hazard model and Kaplan-Meier for overall survival were performed to construct and identify novel models of miRNAs signature for predicting patient survival. 2) Competing risk analysis using the miRNAs signature was conducted to clarify its association with metastatic distributions. 3) Gene Set Enrichment Analysis (GSEA) was performed to identify the genome-epigenome significance of the miRNAs signature. Results: 1) Utilizing Cox model on TCGA cohort, we established a novel risk scoring system with three miRNAs signatures (miR-19a, miR-93, and miR-106a) that identified the patients population with extremely poor overall survival (p = 0.0004; 5-y survival rate, 49.2%). This result was reproduced in two other completely independent cohorts with microarray datasets (GSE19536, p = 0.0009; GSE22220, p = 0.0003, respectively). 2) Utilizing competing risk analysis for each metastatic sites of breast cancer, we found that the patients with bone metastasis demonstrated significantly high scores (p = 0.0052). The evaluation also showed a statistical tendency of association with lung metastasis (p = 0.0854). 3) We found that high score is associated with several critical gene sets such as angiogenesis (p < 0.0001) or epithelial mesenchymal transition (p = 0.0155) by GSEA that suggests that high signature score is associated with enhanced metastasis in breast cancer patients. Conclusions: We established a miRNAs signature scoring system to predict bone metastasis and poor overall survival in breast cancer using novel integrated transcriptomics concept. Citation Format: Tstutomu Kawaguchi, Li Yan, Qianya Qi, Song Liu, Kazuaki Takabe. Novel microRNA signature score to predict bone metastasis and prognosis of breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4436. doi:10.1158/1538-7445.AM2017-4436