Abstract
IntroductionLung 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.MethodsWe 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.ResultsA 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.ConclusionsThe present study demonstrated that identified four-lncRNA signature can be used as an independent prognostic biomarker for the prediction of survival of LUAD patients.
Highlights
Lung cancer is one of the most common cancers worldwide [1]
Multivariate Cox regression analysis based on age, sex, and AJCC stage identified four long noncoding RNA (lncRNA) as independent prognostic biomarkers for lung adenocarcinoma (LUAD) patients
The negative coefficient estimated for the remaining lncRNA (AC119424.1) suggested that high expression level was associated with longer survival
Summary
Lung cancer is one of the most common cancers worldwide [1]. Adenocarcinoma accounts for 40% of all lung cancers [2]. Worsening of environmental pollution is associated with an increase in the number of patients with the disease. Many new methods are currently used to diagnose and treat this disease [3]. Epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase are two key oncogenes that trigger lung adenocarcinoma (LUAD) [4–6]. Overall survival (OS) time for LUAD is less than 5 years because of aggressive properties of the tumor and a lack of effective early diagnostic and prognostic biomarkers [7]. There are only a few prognostic markers for LUAD, and identification of valuable prognostic indicators for clinical treatment is very important
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