Metabolic genes have been reported to act as crucial roles in tumor progression. Lung adenocarcinoma (LUAD) is one of the most common cancers worldwide. This study aimed to predict the potential mechanism and novel markers of metabolic signature in LUAD. The gene expression profiles and the clinical parameters were obtained from The Cancer Genome Atlas-Lung adenocarcinoma (TCGA-LUAD) and Gene Expression Omnibus data set (GSE72094). A total of 105 differentially expressed metabolic genes of intersect expression in TCGA-LUAD and GSE72094 were screened by R language. Univariate Cox regression model found 18 survival-related genes and then the least absolute shrinkage and selection operator model was successfully constructed. Six significant genes prognostic model was validated though independent prognosis analysis. The model revealed high values for prognostic biomarkers by time-dependent receiver operating characteristic (ROC) analysis, risk score, Heatmap, and nomogram. In addition, Gene Set Enrichment Analysis showed that multiplex metabolism pathways correlated with LUAD. Furthermore, we found the six genes aberrantly expressed in LUAD samples. Our study showed that metabolism pathways play important roles in LUAD progression. The six metabolic genes could predict potential prognostic and diagnostic biomarkers in LUAD.
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