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

被引:33
|
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
来源
ONCOTARGETS AND THERAPY | 2019年 / 12卷
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
相关论文
共 50 条
  • [1] A seven-gene signature to predict the prognosis of oral squamous cell carcinoma
    Ribeiro, Ilda Patricia
    Esteves, Luisa
    Santos, Ana
    Barroso, Leonor
    Marques, Francisco
    Caramelo, Francisco
    Melo, Joana Barbosa
    Carreira, Isabel Marques
    ONCOGENE, 2021, 40 (22) : 3859 - 3869
  • [2] A seven-gene signature to predict the prognosis of oral squamous cell carcinoma
    Ilda Patrícia Ribeiro
    Luísa Esteves
    Ana Santos
    Leonor Barroso
    Francisco Marques
    Francisco Caramelo
    Joana Barbosa Melo
    Isabel Marques Carreira
    Oncogene, 2021, 40 : 3859 - 3869
  • [3] A seven-gene prognostic signature for rapid determination of head and neck squamous cell carcinoma survival
    Shen, Sipeng
    Bai, Jianling
    Wei, Yongyue
    Wang, Guanrong
    Li, Qingya
    Zhang, Ruyang
    Duan, Weiwei
    Yang, Sheng
    Du, Mulong
    Zhao, Yang
    Christiani, David C.
    Chen, Feng
    ONCOLOGY REPORTS, 2017, 38 (06) : 3403 - 3411
  • [4] Identification of Seven-Gene Hypoxia Signature for Predicting Overall Survival of Hepatocellular Carcinoma
    Bai, Yuping
    Qi, Wenbo
    Liu, Le
    Zhang, Jing
    Pang, Lan
    Gan, Tiejun
    Wang, Pengfei
    Wang, Chen
    Chen, Hao
    FRONTIERS IN GENETICS, 2021, 12
  • [5] A Seven-Gene Signature with Close Immune Correlation Was Identified for Survival Prediction of Lung Adenocarcinoma
    Zou, Xuan
    Hu, Zhihuang
    Huang, Changjing
    Chang, Jianhua
    MEDICAL SCIENCE MONITOR, 2020, 26
  • [6] A novel seven-gene signature as Prognostic Biomarker in Hepatocellular Carcinoma
    Xie, Hui
    Liu, Shouping
    Zhang, Ziying
    Chen, Peng
    Tao, Yongguang
    JOURNAL OF CANCER, 2020, 11 (19): : 5768 - 5781
  • [7] Identification of a seven-miRNA signature as prognostic biomarker for lung squamous cell carcinoma
    Gao, Xujie
    Wu, Yupeng
    Yu, Wenwen
    Li, Hui
    ONCOTARGET, 2016, 7 (49) : 81670 - 81679
  • [8] A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma
    Wang, Junli
    Zhang, Qi
    Shi, Fukang
    Yadav, Dipesh Kumar
    Hong, Zhengtao
    Wang, Jianing
    Liang, Tingbo
    Bai, Xueli
    FRONTIERS IN GENETICS, 2021, 12
  • [9] Development and Validation of a Seven-Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma
    Zhang, Yingqing
    Zhang, Xiaoping
    Lv, Xiaodong
    Zhang, Ming
    Gao, Xixi
    Liu, Jialiang
    Xu, Yufen
    Fang, Zhixian
    Chen, Wenyu
    BIOMED RESEARCH INTERNATIONAL, 2020, 2020
  • [10] A seven-gene signature model predicts overall survival in kidney renal clear cell carcinoma
    Ling Chen
    Zijin Xiang
    Xueru Chen
    Xiuting Zhu
    Xiangdong Peng
    Hereditas, 157