Identification of a six-gene metabolic signature predicting overall survival for patients with lung adenocarcinoma

PeerJ

article

Yubo Cao¹  Xiaomei Lu²  Yue Li¹  Jia Fu¹  Hongyuan Li¹  Xiulin Li¹  Ziyou Chang¹  Sa Liu¹ 

[1] Department of Medical Oncology, The Fourth Affiliated Hospital of China Medical University;Department of Pathophysiology, China Medical University

关键词: Lung adenocarcinoma;    Metabolic signature;    Overall survival;    Prognostic model;    TCGA;    GEO;   

DOI  :  10.7717/peerj.10320

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

BackgroundLung cancer is the leading cause of cancer-related deaths worldwide. Lung adenocarcinoma (LUAD) is one of the main subtypes of lung cancer. Hundreds of metabolic genes are altered consistently in LUAD; however, their prognostic role remains to be explored. This study aimed to establish a molecular signature that can predict the prognosis in patients with LUAD based on metabolic gene expression.MethodsThe transcriptome expression profiles and corresponding clinical information of LUAD were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. The differentially expressed genes (DEGs) between LUAD and paired non-tumor samples were identified by the Wilcoxon rank sum test. Univariate Cox regression analysis and the lasso Cox regression model were used to construct the best-prognosis molecular signature. A nomogram was established comprising the prognostic model for predicting overall survival. To validate the prognostic ability of the molecular signature and the nomogram, the Kaplan–Meier survival analysis, Cox proportional hazards model, and receiver operating characteristic analysis were used.ResultsThe six-gene molecular signature (PFKP, PKM, TPI1, LDHA, PTGES, and TYMS) from the DEGs was constructed to predict the prognosis. The molecular signature demonstrated a robust independent prognostic ability in the training and validation sets. The nomogram including the prognostic model had a greater predictive accuracy than previous systems. Furthermore, a gene set enrichment analysis revealed several significantly enriched metabolic pathways, which suggests a correlation of the molecular signature with metabolic systems and may help explain the underlying mechanisms.ConclusionsOur study identified a novel six-gene metabolic signature for LUAD prognosis prediction. The molecular signature could reflect the dysregulated metabolic microenvironment, provide potential biomarkers for predicting prognosis, and indicate potential novel metabolic molecular-targeted therapies.

【 授权许可】

CC BY