Extracellular Matrix-receptor Interaction Signaling Genes Associated with Inferior Breast Cancer Survival.

Abstract

Breast cancer is a common type of cancer in women, and metastasis frequently leads to therapy failure. Using next-generation sequencing (NGS), we aspired to identify the optimal differentially expressed genes (DEGs) for use as prognostic biomarkers for breast cancer. NGS was used to determine transcriptome profiles in breast cancer tissues and their corresponding adjacent normal tissues from three patients with breast cancer. Herein, 15 DEGs (fold change >4 and <0.25) involved in extracellular matrix (ECM)-receptor interaction signaling were identified through NGS. Among them, our data indicated that high HMMR expression levels were correlated with a poor pathological stage (p<0.001) and large tumor size (p<0.001), whereas high COL6A6 and Reelin (RELN) expression levels were significantly correlated with an early pathological stage (COL6A6: p=0.003 and RELN: p<0.001). Multivariate analysis revealed that high HMMR and SDC1 expression levels were significantly correlated with poor overall survival (OS; HMMR: adjusted hazard ratio [aHR] 1.93, 95% confidence interval [CI]=1.10-3.41, p=0.023; SDC1: [aHR] 2.47, 95%CI=1.28-4.77, p=0.007) for breast cancer. Combined, the effects of HMMR and SDC1 showed a significant correlation with poor OS for patients with breast cancer (high expression for both HMMR and SDC1: [aHR] 3.29, 95%CI=1.52-7.12, p=0.003). These findings suggest that HMMR and SDC1 involved in the ECM-receptor interaction signaling pathway could act as effective independent prognostic biomarkers for breast ductal carcinoma.