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Research Paper|Volume 11, Issue 2|pp 649—662

A novel six-microRNA-based model to improve prognosis prediction of breast cancer

Jianguo Lai1,2, Hongli Wang1,2, Zihao Pan1,3, Fengxi Su1,2
  • 1Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
  • 2Breast Tumor Center, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
  • 3Department of Thoracic Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
Received: October 30, 2018Accepted: January 5, 2019Published: January 30, 2019
https://doi.org/10.18632/aging.101767

Copyright: © 2019 Lai et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Current tumor-node-metastasis (TNM) stage is unable to accurately predict the overall survival (OS) in breast cancer (BC) patients. This study aimed to construct a microRNA (miRNA)-based model to improve survival prediction of BC. We confirmed 99 differentially expressed miRNAs (DEMs) in 1044 BC samples compared to 102 adjacent normal breast tissues from The Cancer Genome Atlas (TCGA) database. Prognostic DEMs were used to establish a miRNA-based nomogram via Cox regression model. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses (KEGG) were executed to analyze target genes of miRNAs. A six-miRNA signature was screened to effectively distinguish high-risk patients in the primary and validation cohort (all P<0.001). Furthermore, we established a novel prognostic model incorporating the six-miRNA signature and clinical risk factors to predict 5-year OS of BC. Time-dependent receiver operating characteristic analysis suggested that the predictive accuracy of the six-miRNA-based nomogram was distinctly higher than that of TNM stage (0.758 vs 0.650, P<0.001). GO and KEGG pathway analyses showed that the 39 target genes mainly enrichment in protein binding, cytoplasm and MAPK signaling pathway. Our six-miRNA-based model is a reliable prognostic tool for survival prediction and provides information for individualized treatment decisions in BC patients.