Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients

Abstract

Objective: To identify a multi-gene prognostic factor in patients with lung adenocarcinoma (LUAD). Materials and methods Prognosis-related genes were screened in the TCGA-LUAD cohort. Then, patients in this cohort were randomly separated into training set and test set. Least absolute shrinkage and selection operator (LASSO) regression was performed to the penalized the Cox proportional hazards regression (CPH) model on the training set, and a prognostication combination based on the result of LASSO analysis was developed. By performing Kaplan-Meier curve analysis, univariate and multivariable CPH model on the overall survival (OS) as well as recurrence free survival (RFS), the prognostication performance of the multigene combination were evaluated. Moreover, we constructed a nomogram and performed decision curve analysis to evaluate the clinical application of the multigene combination. Results We obtained 99 prognosis-related genes and screened out a 4-gene combination (including CIDEC, ZFP3, DKK1, and USP4) according to the LASSO analysis. The results of survival analyses suggested that patients in the 4-gene combination low-risk group had better OS and RFS than those in the 4-gene combination high-risk group. The 4-gene mentioned was demonstrated to be independent prognostic factor of patients with LUAD in the training set(OS, HR=11.962, P<0.001; RFS, HR=9.281, P<0.001) and test set (OS, HR=5.377, P=0.003; RFS, HR=2.949, P=0.104). More importantly, its prognosis performance was well in the validation set (OS, HR=0.955, P=0.002; RFS, HR=1.042, P<0.001). Conclusions We introduced a 4-gene combination which could predict the survival of LUAD patients and might be an independent prognostic factor in LUAD.

Keywords: least absolute shrinkage and selection operator; lung adenocarcinoma; prognostication; survival analysis.

Figure 1

Time-Dependent ROC Curve of 4-gene combination. (A) ROC in the training set. (B) ROC in the test set. (C) ROC in the validation set.

Figure 2

Characteristics of the 4-gene combination of the discovery cohort. (A) Risk score (On the left is the low-risk group and on the right is the high-risk group). (B) Survival time in days (Red dot indicates Alive, blue dot indicates death). (C) Gene expression heatmap (The blue color is the low-risk group and the red color is the high-risk group)

Figure 3

The correlations between the 4-gene combination and the overall survival (OS) and relapse-free survival (RFS) of patients with LUAD. (A) OS in the training set. (B) OS in the test set. (C) RFS in the training set. (D) RFS in the test set.

Figure 4

Kaplan-Meier curve survival analysis on validation set. (A) OS in the validation set. (B) RFS in the validation set.

Figure 5

Functional enrichment analysis of 99 genes. (A) GO enrichment analysis. (B) KEGG enrichment analysis. GO:0045104 intermediate filament cytoskeleton organization; GO:0033137∼negative regulation of peptidyl-serine phosphorylation; GO:0046627∼negative regulation of insulin receptor signaling pathway; GO:0032147∼activation of protein kinase activity; GO:0032091∼negative regulation of protein binding; GO:0007612∼learning; GO:0097151∼positive regulation of inhibitory postsynaptic potential; GO:0042753∼positive regulation of circadian rhythm; GO:0090244∼Wnt signaling pathway involved in somitogenesis; GO:0090331∼negative regulation of platelet aggregation; GO:0031115∼negative regulation of microtubule polymerization; GO:0042355∼L-fucose catabolic process; GO:0035556∼intracellular signal transduction. hsa01100∼Metabolic pathways; hsa04727∼GABAergic synapse.

Figure 6

Nomogram construction based on 4-gene combination.

Figure 7

The decision curve analysis of the 4-gene combination.