Comprehensive Analysis and Validation of Competing Endogenous RNA Network and Tumor-infiltrating Immune Cells in Lung Adenocarcinoma

Abstract

Objective: The potential pathogenesis of LUAD remains largely unknown. In the present study, we evaluated the competing endogenous RNA (ceRNA) regulatory network and tumorinfiltrating immune cells in LUAD. Methods: We obtained the RNA profiles and corresponding clinical information of LUAD patients from the TCGA data portal, and identified differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs), and miRNAs (DEmiRNAs) between LUAD samples and normal controls to build a ceRNA network. Additionally, the CIBERSORT algorithm was employed to analyze the patterns of immune cell infiltration. Then, two survival-predicting models were constructed based on the ceRNA network and tumor-infiltrating immune cells, which were validated by an independent GEO dataset GSE50081. Moreover, the correlation between prognosis-related ceRNAs and immune cells was also evaluated. Results: In total, 484 LUAD samples and 59 normal controls were included in this study, and 15 DEmiRNAs, 94 DEmRNAs, and 7 DElncRNAs were integrated to construct the ceRNA network of LUAD. Meanwhile, differentially expressed tumor-infiltrating immune cells were also identified, and the expressions of monocytes and regulatory T cells were related to the overall survival (OS) of LUAD patients. Moreover, the prognostic prediction model based on ceRNA network or tumor-infiltrating immune cells exhibited significant power in predicting the survival of LUAD patients. Furthermore, co-expression analysis revealed that some prognosis-related ceRNAs, such as CCT6A, E2F7, SLC16A1, and SNHG3, were positively or negatively correlated with several tumorinfiltrating immune cells, such as monocytes and M1 macrophages. Conclusions: This study improves our understanding of the pathogenesis of LUAD and is helpful in exploring the potential therapeutic targets and prognostic biomarkers for LUAD.