Haoya Xu1,2, Ruoyao Zou1,2, Jiyu Liu1,2, Liancheng Zhu1,2. 1. Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang 110004, Liaoning, China. 2. Key Laboratory of Maternal-Fetal Medicine of Liaoning Province and Key Laboratory of Obstetrics and Gynecology of Higher Education of Liaoning Province, Shenyang 110004, Liaoning, China.
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.
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.
Authors: Toshinori Hinoue; Daniel J Weisenberger; Christopher P E Lange; Hui Shen; Hyang-Min Byun; David Van Den Berg; Simeen Malik; Fei Pan; Houtan Noushmehr; Cornelis M van Dijk; Rob A E M Tollenaar; Peter W Laird Journal: Genome Res Date: 2011-06-09 Impact factor: 9.043
Authors: Francisco J Enguita; Ana Lúcia Leitão; J Tyson McDonald; Viktorija Zaksas; Saswati Das; Diego Galeano; Deanne Taylor; Eve Syrkin Wurtele; Amanda Saravia-Butler; Stephen B Baylin; Robert Meller; D Marshall Porterfield; Douglas C Wallace; Jonathan C Schisler; Christopher E Mason; Afshin Beheshti Journal: Theranostics Date: 2022-05-09 Impact factor: 11.600