Journal of Shandong University (Health Sciences) ›› 2021, Vol. 59 ›› Issue (1): 64-71.doi: 10.6040/j.issn.1671-7554.0.2020.1033

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Predicting colon cancer prognosis genes and clinical application value based on TCGA database

ZHEN Qiulai1,2, LYU Xinran3, YE Hui1, DING Xuchao3, CHAI Xiaoxue1, HU Xin1, ZHOU Ming1, CAO Lili1,3   

  1. 1. Department of Oncology, Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University, Shandong Provincial Key Laboratory for Rheumatic Disease and Translational Medicine, Jinan 250014, Shandong, China;
    2. Department of Blood Transfusion, Central Hospital of Zibo Mining Group Co., Ltd., Zibo 255120, Shandong, China;
    3. Department of Oncology, The First Affiliated Hospital of Shandong First Medical University, Jinan 250014, Shandong, China
  • Published:2021-01-09

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Abstract: Objective To screen the prognostic genes, identify risks and predict prognosis by excavating colon cancer data from TCGA database. Methods The RNA expression data and clinical information of colon cancer patients were downloaded from TCGA database. A proportional hazard regression model was constructed and a risk scoring formula was formed after univariate Cox and multivariate Cox regression analyses. The patients were divided into high-risk and low-risk groups based on the median risk score to determine the mortality risk. The receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to verify the evaluation performance of the model. Survival analysis of prognosis-related genes was performed using R language. The differentially expressed genes were analyzed using GO function and KEGG pathway enrichment. Results Of the 5 544 differentially expressed genes, 27 were associated with overall survival, and 11 were screened to construct the prognostic model, including GABRD, FAM132B, LRRN4, RP11-400N13.2, RP11-108K3.2, RNU6-403P, RP11-429J17.8, LINC01296, RP11-190J1.3, AC002076.10 and CTC-573N18.1. ROC analysis showed that the 5-year survival rate was 39.5%(95%CI: 29.5-53.0)in the high-risk group and 89.6%(95%CI: 82.2-97.7)in the low-risk group, with AUC being0.827, indicating that the model could effectively distinguish patients with high and low risks. Conclusion The risk score obtained from the Cox proportional hazard model genes combined with clinical information can be used to evaluate the prognosis and survival of patients with colon cancer.

Key words: TCGA database, Colon cancer, RNA, Cox proportional hazard model, Survival

CLC Number: 

  • R574.62
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