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. 2015:2015:842784.
doi: 10.1155/2015/842784. Epub 2015 Oct 11.

A Five-Gene Signature Predicts Prognosis in Patients with Kidney Renal Clear Cell Carcinoma

Yueping Zhan  1 , Wenna Guo  1 , Ying Zhang  2 , Qiang Wang  3 , Xin-jian Xu  4 , Liucun Zhu  1
Affiliations

A Five-Gene Signature Predicts Prognosis in Patients with Kidney Renal Clear Cell Carcinoma

Yueping Zhan et al. Comput Math Methods Med. 2015.

Abstract

Kidney renal clear cell carcinoma (KIRC) is one of the most common cancers with high mortality all over the world. Many studies have proposed that genes could be used to predict prognosis in KIRC. In this study, RNA expression data from next-generation sequencing and clinical information of 523 patients downloaded from The Cancer Genome Atlas (TCGA) dataset were analyzed in order to identify the relationship between gene expression level and the prognosis of KIRC patients. A set of five genes that significantly associated with overall survival time was identified and a model containing these five genes was constructed by Cox regression analysis. By Kaplan-Meier and Receiver Operating Characteristic (ROC) analysis, we confirmed that the model had good sensitivity and specificity. In summary, expression of the five-gene model is associated with the prognosis outcomes of KIRC patients, and it may have an important clinical significance.

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Figures

Figure 1
Figure 1
Random survival forests-variable hunting analysis reveals the error rate for the data as a function of trees (a) and the importance values for predictors (b). Importance values show the impact of genes on the model.
Figure 2
Figure 2
Kaplan-Meier curves with two-sided log-rank test show relationship between the risk score resulting from five genes and patients survival. Using the median risk score as a cut-off, patients were divided into the high-risk score and low-risk score. (a) Kaplan-Meier curves for training set patients (n = 262); (b) Kaplan-Meier curves for testing set patients (n = 261). The two-sided log-rank tests were used to determine the survival differences between the high-risk score and low-risk score.
Figure 3
Figure 3
Receiver Operating Characteristic (ROC) analysis of the five-gene signature. The AUROC was 0.783 (p < 0.001), showing that the five-gene model has high sensitivity (true positive rate) and specificity (true negative rate) in predicting the survival time of KIRC patients.
See this image and copyright information in PMC

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