Prognostic Implication of a Metabolism-Associated Gene Signature in Lung Adenocarcinoma.

摘要: Lung cancer is the most common worldwide, leading to high mortality each year. Metabolic pathways play a vital role in initiation and progression of lung cancer. We aimed establish prognostic prediction model for adenocarcinoma (LUAD) patients based on metabolism-associated gene (MTG) signature. Differentially expressed (DE)-MTGs were screened from The Cancer Genome Atlas (TCGA) LUAD cohorts. Univariate Cox regression analysis was performed these DE-MTGs identify genes significantly correlated with prognosis. Least absolute shrinkage selection operator (LASSO) resulting an optimal risk model. Survival used assess ability value signature further validated independent Gene Expression Omnibus (GEO) datasets. A 13 metabolic identified as factor. Kaplan-Meier survival demonstrated good performance both TCGA training GEO validation Finally, nomogram incorporating clinical parameters constructed help individualize outcome predictions. calibration curves showed excellent agreement between actual predicted survival.