Abstract
BackgroundLung adenocarcinoma (LUAD) is a major cause of cancer death. Therefore, identifying potential prognostic risk factors is critical to improve the survival of patients with LUAD.MethodsHere, relevant datasets were downloaded from TCGA and GEO databases to screen the differentially expressed genes (DEGs). Univariate Cox analysis, LASSO regression analysis and multivariate Cox analysis were conducted on the DEGs combined with TCGA clinical data, and finally a risk assessment model based on 10 feature genes was constructed.ResultsThe prognosis of patients was evaluated after the patients were grouped based on the median risk score and the results showed that the survival time of patients in the high-risk group was significantly shorter than that in the low-risk group. ROC analysis showed that the AUC values of the 1, 3, 5-year survival were 0.753, 0.724, and 0.73, respectively, indicating that the model was precise in predicting the prognosis, which was also verified in the external dataset GSE72094. In addition, a significant correlation was found between the risk score and the clinical stages of LUAD, that is, a later stage always corresponded to a higher risk score. Then, we performed survival analysis on the 10 feature genes independently in the TCGA-LUAD dataset through the GEPIA database, finding that the high expression of 6 genes (COL5A2, PLEK2, BAIAP2L2, S100P, ZIC2, SFXN1) was associated with the poor prognosis of LUAD patients.ConclusionTo sum, this study established a 10-gene risk assessment model and further evaluated its value in predicting LUAD prognosis, which provided a new method for the prognosis prediction of LUAD.
Highlights
Lung adenocarcinoma (LUAD) is a major cause of cancer death
differentially expressed genes (DEGs) screening mRNA expression profiles and clinical data of LUAD were downloaded from TCGA database
Identification of DEGs and GO and KEGG pathway enrichment analyses mRNA expression profiles and clinical data of LUAD were downloaded from TCGA database, and eventually 3608 DEGs were obtained by differential analysis using R-package (Fig. 1a)
Summary
Lung adenocarcinoma (LUAD) is a major cause of cancer death. Identifying potential prognostic risk factors is critical to improve the survival of patients with LUAD. Lung cancer had become the most frequently diagnosed cancers worldwide, according to the latest cancer statistics released in 2018 [1]. Despite the continuous improvement in LUAD treatment, the 5-year overall survival (OS) rate is still at a low level with unoptimistic prognosis [7, 8]. Histopathology is often successful in predicting the prognosis of lung cancer patients, but it is limited as individual differences in patients with the same pathology would cause different outcomes. Combined with existing prognostic methods, new molecular biomarkers are considered to have the capability of improving prognosis and treating LUAD appropriately.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have