A six-microRNA signature to predict outcomes of patients with gastric cancer

FEBS Open Bio. 2019 Jan 31;9(3):538-547. doi: 10.1002/2211-5463.12593. eCollection 2019 Mar.

Abstract

Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA expression profiles of 385 GC patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival-related microRNA and then constructed a microRNA signature-based prognostic model. The accuracy of the model was evaluated and validated through Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic microRNA. Finally, a prognostic model based on a six-microRNA (miRNA-100, miRNA-374a, miRNA-509-3, miRNA-668, miRNA-549, and miRNA-653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high-risk and low-risk patients and predict 3-year and 5-year survival. The six-microRNA signature was also an independent prognostic marker, and enrichment analysis suggested that the microRNA may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six-microRNA signature can be used to accurately predict the prognosis of GC patients.

Keywords: gastric cancer; microRNA; overall survival; prognosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Biomarkers, Tumor / genetics*
  • Female
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • MicroRNAs / genetics*
  • ROC Curve
  • Stomach Neoplasms / diagnosis
  • Stomach Neoplasms / genetics*

Substances

  • Biomarkers, Tumor
  • MicroRNAs