Abstract
BACKGROUND: There are many prognostic markers for lung adenocarcinoma (LUAD). However, studies on the prognosis of LUAD by radiotherapy immune-related long noncoding RNAs (lncRNAs) are extremely rare. METHODS: We have compiled 1121 radiotherapy susceptibility differential genes and 6195 immune-related genes. After that, we screened radiotherapy-immunity lncRNAs associated with proliferation by co-expression, univariate, least absolute shrinkage selection operator regression (LASSO), and multivariate analysis of variance. Finally, we constructed a prognostic model based on 6 lncRNAs, and verified the accuracy of the predictive model by ROC and C index. In addition, we used the constructed scoring model to analyze the model's association with the characteristics of immune cell infiltration, immune checkpoint and drug sensitivity. Finally, the whole sample was divided into 2 clusters to further distinguish hot and cold tumors. RESULTS: We constructed a risk score model built on 6 prognostically relevant lncRNAs. Patients were categorized into high-risk and low-risk patients based on median scores in the Train group. We found that people in the high-risk group had a lower survival rate than those in the low-risk group. However, those in the high-risk group were more sensitive to chemotherapy, targeted drugs and also more sensitive to immunotherapy drugs. Based on the line graphs of T, N, Age, Stage and Risk, the corresponding scores can be summed up to visualize the survival rate of patients at 1, 3 and 5 years. Gene set enrichment analysis (GSEA) suggested that radiotherapy-immunity-related lncRNA might be related to pathways such as cell cycle, T cell receptor signaling pathway. It is noteworthy that in our study, cluster 1 was considered to be a hot tumor more sensitive to immunotherapy. CONCLUSION: In summary, we constructed a risk score model built on six radiosensitivity and immune-related lncRNAs, which is expected to be a potential predictive biomarker for radiosensitivity and LUAD prognosis.