Abstract
Background Herein, we tried to develop a prognostic prediction model for patients with LUAD based on the expression profiles of lipid metabolism-related genes (LMRGs). Methods Molecular subtypes were identified by non-negative matrix factorization (NMF) clustering. The overall survival (OS) predictive gene signature was developed and validated internally and externally based on online data sets. Time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier curve, nomogram, restricted mean survival time (EMST), and decision curve analysis (DCA) were used to assess the performance of the gene signature. Results We identified three molecular subtypes in LUAD with distinct characteristics on immune cells infiltration and clinical outcomes. Moreover, we confirmed a seven-gene signature as an independent prognostic factor for patients with LUAD. Calibration and DCA analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the gene signature. In addition, the nomogram showed higher robustness and clinical usability compared with four previously reported prognostic gene signatures. Conclusions Findings in the present study shed new light on the characteristics of lipid metabolism within LUAD, and the established seven-gene signature can be utilized as a new prognostic marker for predicting survival in patients with LUAD.
Highlights
Lung cancer is the leading cause of cancer death worldwide with a five-year survival rate of advanced-stage patients less than 5% [1, 2]
Lung cancer cells have accelerated lipid metabolism than normal lung respiratory epithelium [25]. erefore, lipid metabolism alteration may be a potential indicator of tumor malignancy and prognosis
In order to better understand the biological characteristics of lung adenocarcinoma (LUAD), we classified LUAD into three subtypes based on a comprehensive analysis of lipid metabolism-related genes (LMRGs) expression profiles in the TCGA LUAD data set
Summary
We tried to develop a prognostic prediction model for patients with LUAD based on the expression profiles of lipid metabolism-related genes (LMRGs). Time-dependent receiver operating characteristic (ROC) curve, Kaplan–Meier curve, nomogram, restricted mean survival time (EMST), and decision curve analysis (DCA) were used to assess the performance of the gene signature. We identified three molecular subtypes in LUAD with distinct characteristics on immune cells infiltration and clinical outcomes. We confirmed a seven-gene signature as an independent prognostic factor for patients with LUAD. Calibration and DCA analysis plots indicated the excellent predictive performance of the prognostic nomogram constructed based on the gene signature. Findings in the present study shed new light on the characteristics of lipid metabolism within LUAD, and the established seven-gene signature can be utilized as a new prognostic marker for predicting survival in patients with LUAD
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