Abstract
BackgroundIncreasing 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. We aimed at developing alncRNA signature to improve prognosis prediction of gastric cancer (GC).MethodsUsing a lncRNA-mining approach, we 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). We established a set of 24-lncRNAs that were significantly associated with the disease free survival (DFS) in the test series.ResultsBased 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12943-016-0544-0) contains supplementary material, which is available to authorized users.
Highlights
Increasing evidence suggests long non-coding RNAs are frequently aberrantly expressed in cancers, few related lncRNA signatures have been established for prediction of cancer prognosis
Identification of prognostic lncRNA genes from the test series The 300 gastric cancer (GC) samples were randomly assigned to a test series (n = 180) or a validation series (120)
By subjecting the lncRNA expression data of the test series to univariable Cox regression proportional hazards regression analysis using Biometric Research Branch-Array (BRB-Array) Tools, we identified a set of 63 genes whose parameter P-value were less than 0.01
Summary
Increasing evidence suggests long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers, few related lncRNA signatures have been established for prediction of cancer prognosis. Increasing evidence suggests that the aberrant expressions of lncRNAs have been associated with human cancers [16,17,18], and some of them have been implicated in diagnosis and prognostication [19, 20]. Several prognostic biomarkers for GC have been undergoing or tested in clinical trials such as Fibroblast Growth Factor Receptor (FGFR) [21], Human Epidermal Growth Factor Receptor 2 (HER2) [22], Epidermal Growth Factor Receptor (EGFR) [23], Hepatocyte Growth Factor Receptor (HGFR) [24], etc, many more potential and valuable molecular biomarkers are urgent to be discovered and identified to improve the clinical outcome of patients with GC.
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