Abstract
Purpose To identify mRNA expression-based stemness index- (mRNAsi-) related genes and build an mRNAsi-related risk signature for endometrial cancer. Methods We collected mRNAsi data of endometrial cancer samples from The Cancer Genome Atlas (TCGA) and analyzed their relationship with the main clinicopathological characteristics and prognosis of endometrial cancer patients. We screened the top 50% of the genes in TCGA for weighted gene correlation network analysis (WGCNA) to explore mRNAsi-related gene sets. Among these mRNAsi-related genes, we further screened for those related to the prognosis of endometrial cancer patients via univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Using stepwise multivariate Cox regression analysis, a stemness index-related risk signature was constructed. Finally, we identified potential prognostic biomarkers for endometrial cancer by combining the GEO database and immunohistochemical staining. Results The mRNAsi of endometrial cancer samples was significantly higher than that of normal samples and was related to the International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, postoperative tumor status, and overall survival of endometrial cancer patients. We identified 21 mRNAsi-related gene modules, and 1,324 genes were obtained from the most relevant module. TCGA samples were divided into training and validation cohorts, and the training cohort was used to construct a nine-mRNAsi-related gene signature (B3GAT2, CD3EAP, DMC1, FRMPD3, LINC01224, LINC02068, LY6H, NR6A1, and TLE2). High-risk and low-risk patients had significant prognostic differences, and the risk signature could accurately predict their 1-, 3-, and 5-year survival. The nomogram composed of risk score and multiple clinicopathological features could accurately predict 1-, 3-, and 5-year survival. Finally, CD3EAP was found to be a novel prognostic biomarker for endometrial cancer. Conclusion Endometrial cancer cell stemness is related to patient prognosis. The nine-gene risk signature is an independent prognostic factor and can accurately predict endometrial cancer patient prognosis.
Highlights
Endometrial cancer is the sixth most common cancer among women worldwide, second only to cervical cancer in the incidence of gynecological malignant tumors [1], and its incidence continues to increase [2]. e International Federation of Gynecology and Obstetrics (FIGO) stage is the most important prognostic factor for endometrial cancer. e 5year survival rate of patients in stage I/II is 74–91%, while that of patients in stages III and IV is only 57–66% and 20–26%, respectively [3]
We evaluated the correlation among the mRNA expression-based stemness index (mRNAsi), clinicopathological features, and endometrial carcinoma patient prognosis. e mRNAsi of endometrial carcinoma was significantly higher than that of normal endometrium (P < 2.22 ×10−16; Figure 1(a))
Erefore, identifying genes related to Endometrial cancer stem cells (ECSCs) and exploring their potential mechanisms of action will aid in understanding the mechanism of endometrial carcinogenesis and may provide a new direction for cancer treatment. e stemness index describes the characteristics of tumor stem cells
Summary
Endometrial cancer is the sixth most common cancer among women worldwide, second only to cervical cancer in the incidence of gynecological malignant tumors [1], and its incidence continues to increase [2]. e International Federation of Gynecology and Obstetrics (FIGO) stage is the most important prognostic factor for endometrial cancer. e 5year survival rate of patients in stage I/II is 74–91%, while that of patients in stages III and IV is only 57–66% and 20–26%, respectively [3]. Erefore, it is important to explore predictive prognostic markers and construct prognostic models to help clinicians prospectively predict patient prognosis and treat them . Endometrial cancer stem cells (ECSCs) can initiate cloning, self-renewal, proliferation, and differentiation and can form tumors that can be serially passaged in vivo [5]. Isolating and identifying ECSC biomarkers and further studying their role in the occurrence and development of endometrial cancer may provide new methods for treating endometrial cancer. Many studies have confirmed that targeting CD55 [6], SMOC-2 [7], and other ECSC stemness markers can help overcome chemotherapy resistance and inhibit tumor cell proliferation. Studies have explored genes related to mRNAsi in a variety of cancers and have analyzed the effects of these genes on cancer patient prognosis [9, 10]
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