Large miRNA survival analysis reveals a prognostic four-biomarker signature for triple negative breast cancer.

Fernando Andrade,Asuka Nakata,André Fujita,Noriko Gotoh

doi:10.1590/1678-4685-gmb-2018-0269

Abstract

Triple negative breast cancer (TNBC) is currently the only major breast tumor subtype without effective targeted therapy and, as a consequence, usually presents a poor outcome. Due to its more aggressive phenotype, there is an urgent clinical need to identify novel biomarkers that discriminate individuals with poor prognosis. We hypothesize that miRNAs can be used to this end because they are involved in the initiation and progression of tumors by altering the expression of their target genes. To identify a prognostic biomarker in TNBC, we analyzed the miRNA expression of a cohort composed of 185 patients diagnosed with TNBC using penalized Cox regression models. We identified a four-biomarker signature based on miR-221, miR-1305, miR-4708, and RMDN2 expression levels that allowed for the subdivision of TNBC into high- or low-risk groups (Hazard Ratio – HR = 0.32; 95% Confidence Interval - CI = 0.11–0.91; p = 0.03) and are also statistically associated with survival outcome in subgroups of postmenopausal status (HR = 0.19; 95% CI = 0.04–0.90; p= 0.016), node negative status (HR = 0.12; 95% CI = 0.01–1.04; p = 0.026), and tumors larger than 2cm (HR = 0.21; 95% CI = 0.05–0.81; p = 0.021). This four-biomarker signature was significantly associated with TNBC as an independent prognostic factor for survival.

Highlights

Breast cancer is the most common cancer among women, with an estimated 246,660 new cases and 40,450 deaths in 2016 in the United States (Siegel et al, 2016)
Our prognostic signature is composed of three microRNAs and one gene that codes for a protein, miR-221, miR-1305, miR-4708, and RMDN2
A prognostic model composed of these three miRNAs and the RMDN2 gene was constructed by using the standard Cox proportional hazard model

Summary

Introduction

Breast cancer is the most common cancer among women, with an estimated 246,660 new cases and 40,450 deaths in 2016 in the United States (Siegel et al, 2016). Predictive molecular biomarkers and targeted therapies are still lacking for the treatment of triple negative breast cancer (TNBC) (Gonzalez-Angulo et al, 2007; Blows et al, 2010; Iwase et al, 2010; The Cancer Genome Atlas Network, 2012). This may be the reason for the low improvement of survival rates of TNBC patients in the last years (Gonzalez-Angulo et al, 2007). A molecular stratification of TNBC based on molecular markers is essential to identify novel targets of drugs

Methods

Results

Conclusion