Construction of an immune-related lncRNA pairs model to predict prognosis and immune landscape of lung adenocarcinoma patients

• Main Authors: Junhui Liu, Hao Wu, Zhaojia Gao, Ming Lou, Kai Yuan
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2021-01-01
• Series: Bioengineered
• Subjects: tcga; immune-related lncrna; lung adenocarcinoma; immune cell infiltration; ici-related biomarkers; chemotherapeutics
• Online Access: http://dx.doi.org/10.1080/21655979.2021.1953215

The model of immune-related lncRNA pairs (IRLPs) seems to be an available predictor in lung adenocarcinoma (LUAD) patients. The aim of our study was to construct a model with IRLPs to predict the survival status and immune landscape of LUAD patients. Based on TCGA-LUAD dataset, a risk assessment model with IRLPs was established. Then, ROC curves were used to assess the predictive accuracy and effectiveness of our model. Next, we identified the difference of survival, immune cell infiltration, immune checkpoint inhibitor-related (ICI-related) biomarkers, and chemotherapeutics between high-risk group and low-risk group. Finally, A nomogram was built for predicting the survival rates of LUAD patients. 464 LUAD samples were randomly and equally divided into a training set and a test set. Six IRLPs were screened out to construct a risk model. K-M analysis and risk-plot suggested the prognosis of high-risk group was worse than low-risk group (p < 0.001). Multivariate analysis shows risk score was independent risk factor of LUAD (p < 0.001). In addition, the expression of immune cell infiltration, ICI-related biomarkers, chemotherapeutics all demonstrate significant difference in two groups. A nomogram was built that could predict the 1-, 3-, and 5-year survival rates of LUAD patients. Our immune-related lncRNA pairs risk model is expected to be a reliable model for predicting the prognosis and immune landscape of LUAD patients.