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. 2018 Jun;7(6):2601-2611.
doi: 10.1002/cam4.1498. Epub 2018 Apr 17.

Establishment of a nine-gene prognostic model for predicting overall survival of patients with endometrial carcinoma

Jianchao Ying  1 , Qian Wang  2 , Teng Xu  1 , Jianxin Lyu  1
Affiliations

Establishment of a nine-gene prognostic model for predicting overall survival of patients with endometrial carcinoma

Jianchao Ying et al. Cancer Med. 2018 Jun.

Abstract

Endometrial carcinoma (EC) is the most common malignant tumor of the female genital tract in developed countries. The prognosis of early stage EC is favorable, but a subset faces high risk of cancer progression or recurrence. EC has a poor prognosis upon progression to advanced or metastatic stages. Therefore, our goal is to build a robust prognostic model for predicting overall survival (OS) in EC patients. In this study, 1571 genes were identified as being associated with OS based on genomewide expression profiles using a training dataset. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that these genes were involved in various cancer-related signaling pathways. Nine signature genes were further selected using stepwise selection, and their potential role in the development of EC was demonstrated by performing differential expression analysis between EC and normal uterine tissues. A prognostic model that aggregated these nine signature genes was ultimately established and effectively divided EC patients into two risk groups. OS for patients in the high-risk group was significantly poorer compared with that of the low-risk group. This nine-gene model was subsequently validated and evaluated using the TCGA dataset and shown to have a high discriminating power to distinguish EC patients with an elevated risk of mortality based on the FIGO staging system and other prognostic factors. This study provides a novel prognostic model for the identification of EC patients with elevated risk of mortality and will help to improve our understanding of the underlying mechanisms involved in prognostic EC factors.

Keywords: Endometrial carcinoma; genomewide expression profiles; overall survival; prognostic model; signature gene.

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Figures

Figure 1
Figure 1
Identification of optimal signature genes for overall survival (OS) prediction in endometrial carcinoma (EC). (A) Functional enrichment analysis of Kyoto Encyclopedia of Genes and Genomes for 1571 genes associated with OS. Only pathways with a P‐value <0.05 are presented. (B) The unsupervised hierarchical clustering heatmap of the training dataset based on the expression profiles of nine signature genes. Patients were categorized into two clusters. (C) Kaplan–Meier curves for patients in two different clusters. (D) The mRNA expression of nine signature genes in 181 EC tissues and 78 normal uterine tissues in the dataset from the UCSC Xena project. The distribution of expression data is represented by a violin plot, and the dashed lines indicate the quartiles. P‐values were calculated by Mann–Whitney U test. (*P < 0.001)
Figure 2
Figure 2
Construction of prognostic model based on nine signature genes. (A) The cross‐validated time‐dependent ROC curve for survival predictions was produced using BRB‐ArrayTools. (B) Kaplan–Meier curves for patients in two risk groups that were partitioned based on the 50th prognostic index percentile.
Figure 3
Figure 3
Performance of the nine‐gene model in overall survival (OS) prediction of endometrial carcinoma (EC) using the validation dataset. (A) The distribution of survival risk score of EC patients in validation dataset. (B) Survival (or censoring) time of EC patients. (C) Clustering heatmap of mRNA expression profiles of the nine signature genes. (D) The ROC curve was generated for 5‐year OS predictions with an AUC of 0.676. The optimal cutoff value (2.261), shown as the gray straight line in A, B, and C, was obtained to divide the patients into low‐ and high‐risk groups. (E) Kaplan–Meier curves for patients in two risk groups. Patients in the high‐risk group exhibited a poorer OS compared with patients in the low‐risk group (HR = 3.589, P < 0.001).
Figure 4
Figure 4
Comparison of survival prediction power of the nine‐gene prognostic model with the FIGO stage. (A) Kaplan–Meier curves for patients in four FIGO stages. A significant difference was observed between 5‐year overall survival (OS) of stage III and stage IV (in advanced stage) patients (P = 0.003), whereas no significant difference was noted between stage I and stage II (in early stage) (P > 0.05). (B) For 521 endometrial carcinoma (EC) patients, advanced stage EC was associated with increased 5‐year mortality compared with early stage EC. (C, D, E, F, G) The EC patients in various stages were divided into high‐ and low‐risk groups based on their survival risk scores. By plotting Kaplan–Meier curves, the nine‐gene model for prediction of 5‐year OS in patients with early stage (C) and advanced stage (D) EC was assessed individually. Similarly, the association between the prognostic model (survival risk) and 5‐year OS in patients with stage I and stage III EC was also evaluated simultaneously (E) or individually (stage I in (F); stage III in (G)). (H) The ROC curves for OS prediction of the FIGO stage, histological type, histological grade, the nine‐gene prognostic model, and the combined model.
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