Construction of a Prognostic Model for Lung Adenocarcinoma Based on Nucleotide Metabolism-Related Genes and Bioinformatics Analysis

Abstract

Abstract Background: Metabolic reprogramming is an important hallmark of cancer. However, it is still uncertain how nucleotide metabolism-related genes (NMRGs) may affect the prognosis of Lung adenocarcinoma (LUAD). Methods: In our study, the LUAD cohorts from the bioinformatics databases were downloaded. Characteristic genes related to prognosis of LUAD patients were obtained through combining differentially expressed analysis, univariate COX analysis, least absolute shrinkage and selection operator (LASSO), and multivariate COX, and the risk model was constructed. Then, the immune infiltration, immunotherapy, and mutations analyses between high and low risk groups were conducted. Finally, drug sensitivity analysis and reverse transcription-polymerase chain reaction (RT-qPCR) was executed to validate the expression of the biomarkers. Results: Based on 4 characteristic genes (RRM2, TXNRD1, NME4, and NT5E), the risk model was established, and the patients were assigned to high/low risk groups. The survival analysis demonstrated that patients in low risk groups had higher survival. The infiltrating abundance of 11 immune cells, the expression of 25 immune checkpoints, TIDE score, Dysfunction score, Exclusion score, IPS, and IPS-CTLA4 were significantly different between two risk groups. Additionally, the survival of patients in low-risk and high-TMB group was the highest. Finally, the IC50 of 124 drugs was considerably different between two risk groups, such as Doramapimod_1042, BMS-754807_2171, MK-2206_1053, etc. Finally, RT-qPCR results showed that RRM2 and NT5E expression was obviously up-regulated and TXNRD1 expression was obviously down-regulated in LUAD. Conclusion: Taken together, this study created a nucleotide metabolism related prognostic characteristic, which was relevant to immune microenvironment and immunotherapy.