Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, however, few related lncRNA signatures have been established for prediction of cancer prognosis. Scientists at Shanghai JiaoTong University aimed at developing a lncRNA signature to improve prognosis prediction of gastric cancer (GC).
Using a lncRNA-mining approach, they performed lncRNA expression profiling in large GC cohorts from Gene Expression Ominus (GEO), including GSE62254 data set (N = 300) and GSE15459 data set (N = 192). They established a set of 24-lncRNAs that were significantly associated with the disease free survival (DFS) in the test series.
Based on this 24-lncRNA signature, the test series patients could be classified into high-risk or low-risk subgroup with significantly different DFS (HR = 1.19, 95 % CI = 1.13-1.25, P < 0.0001). The prognostic value of this 24-lncRNA signature was confirmed in the internal validation series and another external validation series, respectively. Further analysis revealed that the prognostic value of this signature was independent of lymph node ratio (LNR) and postoperative chemotherapy. Gene set enrichment analysis (GSEA) indicated that high risk score group was associated with several cancer recurrence and metastasis associated pathways.
a Gene set enrichment analysis delineates biological pathways and processes correlated with risk score. Cytoscape was used for visualization of the GESA results. Nodes represent enriched gene sets that are grouped and annotated by their similarity according to related gene sets. Enrichment results were mapped as a network of gene sets (nodes). Node size is proportional to the total number of genes within each gene set. Proportion of shared genes between gene sets is represented as the thickness of the green line between nodes. b Box plot of risk score of patients with or without recurrence in entire GSE62254 series excluding patients without available information (N = 283, P < 0.0001).T-test was used to determine the significance of the comparisons
The identification of the prognostic lncRNAs indicates the potential roles of lncRNAs in GC biogenesis. Our results may provide an efficient classification tool for clinical prognosis evaluation of GC.