Construction of a Prognostic Signature of 10 Autophagy-Related lncRNAs in Gastric Cancer

构建胃癌中10种自噬相关lncRNA的预后特征

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Abstract

BACKGROUND: Autophagy plays a double-edged sword role in cancers. LncRNAs could regulate cancer initiation and development at various levels. However, the role of autophagy-related lncRNAs (ARlncs) in gastric cancer (GC) remains indistinct. METHODS: GC gene expression profile and clinical data were acquired from the Cancer Genome Atlas (TCGA). The prognostic signature composed of ARlncs was established via cox regression analysis. Kaplan-Meier (K-M) survival curve was adopted to show overall survival (OS). Independence and reliability of risk signature were visualized by cox regression analysis and ROC curve. A nomogram was constructed and the reliability was analyzed by ROC curve. Immune infiltrating cells and check points were also analyzed. RESULTS: A prognostic signature was constructed which stratified GC patients into high- and low-risk groups according to risk score calculated via the 10 ARlncs including LINC01094, AC068790.7, AC090772.1, AC005165.1, PVT1, LINC00106, AC026368.1, AC090912.3, AC013652.1, UICLM. Patients in high-risk group showed a poor prognosis (p<0.001). Cox regression analysis showed signature was an independent prognostic factor (p<0.001). Areas under curves (AUC) of ROC for risk signature for predicting OS outweighed age, gender, grade, T, M and N, which suggested the reliability of the signature. A nomogram was constructed with risk signature, T, M, N and age and its AUC of ROC for 1-, 3-, and 5-year was 0.700, 0.730, 0.757 respectively, which showed good reliability. Macrophage M2, T cell CD8+ and T cell CD4+ memory resting had greatest difference between the two risk groups according to CIBERSORE-ABS algorithm (p<0.001). CD274 (PD-L1), PDCD1 (PD-1) and PDCD1LG2 (PD-L2) were expressed higher in the high-risk group (p<0.05), which implied that immunotherapy may be a good choice for these patients. CONCLUSION: The risk signature based on 10 ARlncs can serve as an efficacious prognostic predictor and guide the immunotherapies and precise treatment for GC patients.

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