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pmid:31743579
Identification of a 6-lncRNA prognostic signature based on microarray re-annotation in gastric cancer.
Bin Ma · Yongmin Li · Yupeng Ren
Cancer medicine · 2020 doi:10.1002/cam4.2621
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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Therefore, the current study aimed to explore lncRNA-based prognostic biomarkers for GC. LncRNA expression profiles from the Gene Expression Omnibus (GEO) database were first downloaded. After re-annotation of lncRNAs, a univariate Cox analysis identified 177 prognostic lncRNA probes in the training set GSE62254 (n = 225). Multivariate Cox analysis of each lncRNA with clinical characteristics as covariates identified a total of 46 prognostic lncRNA probes. Robust likelihood-based survival and least absolute shrinkage and selection operator (LASSO) models were used to establish a 6-lncRNA signature with prognostic value. Receiver operating characteristic (ROC) curve analyses were employed to compare survival prediction in terms of specificity and sensitivity. Patients with high-risk scores exhibited a significantly worse overall survival (OS) than patients with low-risk scores (log-rank test P-value <.0001), and the area under the ROC curve (AUC) for 5-year survival was 0.77. A nomogram and forest plot were constructed to compare the clinical characteristics and risk scores by a multivariable Cox regression analysis, which suggested that the 6-lncRNA signature can independently make the prognosis evaluation of patients. Single-sample GSEA (ssGSEA) was used to determine the relationships between the 6-lncRNA signature and biological functions. The internal validation set GSE62254 (n = 75) and the external validation set GSE57303 (n = 70) were successfully used to validate the robustness of our 6-lncRNA signature. 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