The Construction And Analysis of ceRNA Network And Patterns of Immune Infiltration In Lung Adenocarcinoma [post]

Jinglong Li, Wenyao Liu, Xiaocheng Dong, Yunfeng Dai, Shaoshen Chen, Enliang Zhao, Yunlong Liu, Hongguang Bao
2021 unpublished
Background: Lung adenocarcinoma (LUAD) is the most common one of lung cancer. Competitive endogenous RNA (ceRNA) may be closely associated with tumor progression. However, studies on ceRNAs and immune cells in LUAD are scarce. Method: The profiles of gene expression and clinical data of LUAD patients were extracted from the TCGA database and separated into two categories: LUADs and adjacent normal tissues. Bioinformatics methods were used to evaluate differentially expressed genes (DEGs) and
more » ... m a ceRNA network. Preliminary verification of clinical specimens was employed to detect the expressions of key biomarkers at the tissue level. Cox and Lasso regressions were used to screen the key genes and halt overfitting, upon which the prognosis prediction nomograms were formed. The interconnection between the risk score and immune components was evaluated using the CIBERSORT algorithm, while the conformation of notable tumor-infiltrating immune cells (TIICs) in the LUAD tissues of the high- and the low-risk group was assessed using the RNA transcript relative subgroup for identifying the tissue types. Finally, co-expression study was used to examine the interconnection between the key genes in the ceRNA networks and the immune cells.Result: A ceRNA network of 115 RNAs was established, and nine key genes were screened to construct a Cox proportional-hazard model for making a prognostic nomogram. This risk-assessment model might serve as an unconstrained factor to forecast the prognosis of LUAD, and it was consistent with the preliminary verification of clinical specimens. The CIBERSORT algorithm was used to screen four highly expressed LUAD-related immune infiltrating cells, identifying five immune cells with significant differences in the LUAD tissues of the high- and low-risk groups. Besides, two pairs of biomarkers associated with the growth of LUAD were found, i.e., E2F7 and macrophage M1 (R = 0.419, p = 1.4e-08) and DBF4 and macrophage M1 (R = 0.282, p < 2.2 e-16); they appeared to be co-expressed.Conclusion: This study identified several important ceRNAs (E2F7 and BNF4) and TIICs (macrophage M1), which might be related to the development and prognosis of LUAD. The established risk-assessment model might help better clinical management.
doi:10.21203/ fatcat:r4kjist2g5agnf6uykmcyl2rxa