Identification of a five‑gene signature for predicting the progression and prognosis of stage I endometrial carcinoma

Abstract

Uterine corpus endometrial carcinoma (UCEC) is often diagnosed at an early clinical stage based on abnormal vaginal bleeding. However, the prognosis of UCEC is poor. The present study was conducted to identify novel tumor grade-related genes with the potential to predict the prognosis and progression of UCEC. A total of three gene expression microarray datasets were downloaded from the Gene Expression Omnibus database, and one RNA-sequencing dataset with corresponding clinical information of patients with UCEC was obtained from The Cancer Genome Atlas database. In summary, 1,447 differentially expressed genes (DEGs) were identified between endometrial cancerous tissues and normal endometrial tissues. Weighted gene co-expression network analysis was performed to assess the associations between DEGs and clinical traits. In total, five genes were found to be highly associated with the tumorigenesis and prognosis of UCEC. Among them, BUB1 mitotic checkpoint serine/threonine kinase B, cyclin B1, cell-division cycle protein 20 and non-SMC condensing I complex subunit G were involved in cell cycle regulation pathways, and DLG-associated protein 5 was involved in the Notch receptor 3 signaling pathway based on functional enrichment analyses. Of the five genes, four were highly expressed in endometrial cancerous tissues compared with normal endometrial tissues at the protein level. In addition, the higher expression of these genes predicted a higher tumor grade and worse overall survival. In conclusion, the present study revealed a 5-gene signature that can be used to predict the progression of UCEC.

N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma

“…Although the study of UCEC treatment has made some progress [41], the mortality continues to rise, seriously threatening women's health. Many markers that can predict the prognosis of UCEC have been found [42]; however, so far, there is no unified index. lncRNAs have the potential to become immunotherapeutic targets and biomarkers for a UCEC prognosis due to the characteristics of its high efficiency, high tissue specificity, and high stability.…”

Development and Clinical Validation of Novel 8-Gene Prognostic Signature Associated With the Proportion of Regulatory T Cells by Weighted Gene Co-Expression Network Analysis in Uterine Corpus Endometrial Carcinoma

“…Previous studies have also found gene prognostic markers closely related to UCEC (68)(69)(70), but it is the first time to construct a model in Treg cells to predict the prognosis of UCEC. AUC is a crucial standard to judge whether a prediction model has good discrimination.…”

Identification of a Four-Gene Signature With Prognostic Significance in Endometrial Cancer Using Weighted-Gene Correlation Network Analysis

“…Depth of myometrial invasion and lymphovascular space invasion is the main predictor of prognosis after surgery ( Brooks et al, 2019 ). During the past decade, considerable progress has been made in understanding the complex molecular and cellular nature of EC, and various key genes have been identified through bioinformatic analyses ( Huo et al, 2019 ; Bian et al, 2020 ; Liu et al, 2020 ). Through WGCNA, we determined the most significant modules using clinical traits.…”