Identification of an Immune-related Seven-lncRNA Signature Predicting Prognosis and Tumor-infiltrating Immune Cells in Lung Adenocarcinoma
Background: Lung adenocarcinoma (LUAD) is a common cancer. Immunotherapy is one of the major treatments but showing diverse efficacy in LUAD. Long non-coding RNAs (lncRNAs) are emerging as important players in immune regulation in cancer. Herein, we identified and validated a prognostic signature of immune-related lncRNAs in LUAD and explored its correlation with tumor-infiltrating immune cells (TIICs) by bioinformatics analysis.Methods: Immune-related lncRNAs were acquired using Pearson
... tion analysis between lncRNAs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and immune genes from the ImmPort website and Molecular Signatures Database. The risk signature was constructed in the TCGA group through univariable Cox, lasso and multivariable Cox regression analyses. The prognostic value of the established risk signature was validated in both TCGA and GEO datasets. The interacted TIICs and immune pathways with each single lncRNA and the risk signature were investigated respectively in ImmLnc database, Cibersortx database and gene set enrichment analysis (GSEA) analyses.Results: A seven immune-related lncRNAs prognostic signature was constructed and it stratified LUAD into high and low risk groups. High risk group showed poorer overall survival (OS) in comparison with low risk group via survival analysis.The seven-lncRNAs signature was closely correlated with various TIICs and immune pathways mostly involved in T cell activation, antigen processing and presentation, chemokines and cytokine receptors.Conclusions: The seven lncRNAs model was identified as a predictable signature for prognosis of LUAD patients probably due to its immunomodulation role. This study might provide a new target for enhancing the efficacy of immunotherapy in this mortal disease.