Abstract
Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A network was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.
Highlights
Gastric cancer (GC) is a malignant tumor initiated from the epithelial cells of gastric mucosa
Identification of robust differentially expressed genes in gastric cancers We developed a multi-step strategy to identify a critical gene signature that is able to distinguish good and bad prognosis for GC patients using publically available datasets (Figure 1)
We sought to identify significantly differentially expressed genes through comparing gene expression between normal and GC tissues using two datasets: TCGA that was generated by RNA sequencing [10] and GSE30727 that was generated by Affymetrix microarray
Summary
Gastric cancer (GC) is a malignant tumor initiated from the epithelial cells of gastric mucosa. GC has been one of the most common malignant tumors in the world and ranks fifth in the incidence rate, following lung cancer, breast cancer, colorectal cancer and prostate cancer [1, 2]. With the advances in science and biotechnology, the level of early diagnosis for GC has been improved to certain extent, which, in turn, significantly improves its five-year survival rate. The five-year survival rate of advanced GC is only about 29.3%, which is due to that GC is prone to relapse and metastasis [1,2,3,4]
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