Introduction: Lung adenocarcinoma (LUAD) is currently one of the most common malignant tumors worldwide. However, there is a lack of long noncoding RNA (lncRNA)-based effective markers for predicting the prognosis of LUAD patients. We identified four lncRNAs that can effectively predict the prognosis of LUAD patients.
Methods: We used data gene expression profile for 446 patients from The Cancer Genome Atlas database. The patients were randomly divided into a training set and a test set. Significant lncRNAs were identified by univariate regression. Then, multivariate regression was used to identify lncRNAs significantly associated with the survival rate. We constructed four-lncRNA risk formulas for LUAD patients and divided patients into high-risk and low-risk groups. Identified lncRNAs subsequently verified in the test set, and the clinical independence of the lncRNA model was evaluated by stratified analysis. Then mutated genes were identified in the high-risk and low-risk groups. Enrichment analysis was used to determine the relationships between lncRNAs and co-expressed genes. Finally, the accuracy of the model was verified using external database.
Results: A four-lncRNA signature (AC018629.1, AC122134.1, AC119424.1, and AL138789.1) has been verified in the training and test sets to be significantly associated with the overall survival of LUAD patients.
Conclusions: The present study demonstrated that identified four-lncRNA signature can be used as an independent prognostic biomarker for the prediction of survival of LUAD patients.
Keywords: bioinformatics; biomarker; lncRNA; lung adenocarcinoma; prognosis.
© 2021 Zhihui Zhang et al., published by De Gruyter.