Molecular profiling has been applied for uterine corpus endometrial carcinoma (UCEC) management for many years. The aim of this study was to explore the role of MCM10 in UCEC and construct its overall survival (OS) prediction models. Data from TCGA, GEO, cbioPotal and COSMIC databases and the methods, such as GO, KEGG, GSEA, ssGSEA and PPI, were employed to bioinformatically detect the effects of MCM10 on UCEC. RT-PCR, Western blot and immunohistochemistry were used to validate the effects of MCM10 on UCEC. Based on Cox regression analysis using the data from TCGA and our clinical data, two OS prediction models for UCEC were established. Finally, the effects of MCM10 on UCEC were detected in vitro. Our study revealed that MCM10 was variated and overexpressed in UCEC tissue and involved in DNA replication, cell cycle, DNA repair and immune microenvironment in UCEC. Moreover, silencing MCM10 significantly inhibited the proliferation of UCEC cells in vitro. Importantly, based on MCM10 expression and clinical features, the OS prediction models were constructed with good accuracy. MCM10 could be an effective treatment target and a prognostic biomarker for UCEC patients. The OS prediction models might help establish the strategies of follow-up and treatment for UCEC patients.
Keywords: MCM10; OS prediction model; TCGA; uterine corpus endometrial carcinoma; variation.
© 2023 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.