Identification of seven-gene signature for prediction of lung squamous cell carcinoma

被引:34
作者
Wang, Zhe [1 ]
Wang, Zhongmiao [1 ]
Niu, Xing [2 ]
Liu, Jie [3 ]
Wang, Zhuning [2 ]
Chen, Lijie [4 ]
Qin, Baoli [1 ]
机构
[1] China Med Univ, Liaoning Canc Hosp & Inst, Canc Hosp, Dept Gastrointestinal Oncol, 44 Xiaoheyan Rd, Shenyang 110042, Liaoning, Peoples R China
[2] China Med Univ, Dept Clin Coll 2, Shengjing Hosp, Shenyang 110004, Liaoning, Peoples R China
[3] China Med Univ, Sci Expt Ctr, Shenyang 110122, Liaoning, Peoples R China
[4] China Med Univ, Dept Clin Coll 3, Shenyang 110122, Liaoning, Peoples R China
关键词
lung squamous cell carcinoma; prognosis; gene set enrichment analysis; Cox regression model; risk score; DNA-DAMAGE RESPONSE; POOR-PROGNOSIS; CANCER; GENES;
D O I
10.2147/OTT.S198998
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background and aim: Lung squamous cell carcinoma (LUSC), is a pathological subtype of lung cancer, accounting for 30% of the lung cancers. A reliable model was constructed, based on the whole gene expression profiles, to predict the prognosis of patients with LUSC. Methods: The RNA-Seq data of LUSC was downloaded from the TCGA database, and differentially expressed genes (p<0.05, vertical bar log2fold change vertical bar >1) were screened out. By univariate and multivariate Cox regression analysis, we identified seven prognosis-related genes. Then, we established a risk score staging system to predict the prognosis of patients with LUSC. Compared with other clinical parameters, the risk score was an independent prognostic factor and had a better performance in predicting prognosis. Finally, GSEA analysis was carried out to determine the enrichment pathway significantly. The risk score models were established by Cox proportional hazard regression analysis; the ROC curve was applied to test the performance of risk score model. All the statistical analysis was accomplished by R packages. Results: In this study, a model was constructed to predict prognosis, which contains seven genes: CSRNP1, CLEC18B, MIR27A, AC130456.4, DEFA6, ARL14EPL, and ZFP42. Based on the model, the risk score of each patient was calculated with LUSC (hazard ratio [HR] =2.673, 95% CI=1.871-3.525). It was found that the risk score can distinguish high-risk and low-risk groups in prognosis of LUSC patients, independently. Furthermore, the model was validated by ROC curves in the testing dataset and the whole dataset. Lastly, by gene set enrichment analysis (GSEA), we showed the main enrichment pathways were DNA damage stimulus, DNA repair, and DNA replication. It was suggested that the risk score may provide a new and reliable method for prognosis prediction. Conclusion: The results of this study suggested that the risk score based on seven-genes could indicate a promising and independent prognostic biomarker for LUSC patients.
引用
收藏
页码:5979 / 5987
页数:9
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