Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis

Author:

Liu Yun1ORCID,Chen Peigen2ORCID,Li Mengxiong1ORCID,Fei Hui1ORCID,Huang Jinfeng1ORCID,Zhao Tingting1ORCID,Li Tian1ORCID

Affiliation:

1. Department of Obstetrics and Gynecology, The Seventh Affiliated Hospital, Sun Yat-sen University, China

2. Reproductive Medicine Center, The Sixth Affiliated Hospital, Sun Yat-sen University, China

Abstract

Background. Cancer stem cells play an important role in endometrial cancer (EC). It is closely related to self-renewal and therapeutic resistance of EC. Methods. In this study, WGCNA (weighted gene coexpression network analysis) was used to analyze the relationship between genes and clinical features. We also performed immune cell infiltration analysis of a key module by using ImmuCellAI (Immune Cell Abundance Identifier). Then, key genes were verified in the GEO database. Finally, causal relationship analysis and protein-protein interaction analysis were performed in DisNor tool and STRING. Result. The mRNA expression-based stemness index (mRNAsi) is significantly lower in normal tissues and is significantly higher in individuals with stage IV or high-grade cancer and those who are obese or postmenopausal. Nineteen key genes (ORC6, C1orf112, RAD54L, SGO2, BUB1, PLK4, KIF18B, BUB1B, TTK, NCAPG, XRCC2, CENPF, KIF15, RACGAP1, ARHGAP11A, TPX2, KIF14, KIF4A, and NCAPH) that were enriched mainly in terms related to the cell cycle and DNA replication were selected by weighted gene coexpression network analysis (WGCNA). Based on the key modules, the numbers of NKT cells, NK cells, and neutrophils in the normal group were significantly higher than those in the cancer group. PLK1, CDK1, and MAD2L1, which were correlated with upstream genes, may be an regulated upstream of key genes. Conclusion. PLK1, CDK1, and MAD2L1 which were strongly correlated with upstream genes may be a regulated upstream of key genes.

Publisher

Hindawi Limited

Subject

Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine

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