Cargando…

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

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 feature...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Yun, Chen, Peigen, Li, Mengxiong, Fei, Hui, Huang, Jinfeng, Zhao, Tingting, Li, Tian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025127/
https://www.ncbi.nlm.nih.gov/pubmed/33859719
http://dx.doi.org/10.1155/2021/6653295
_version_ 1783675449089458176
author Liu, Yun
Chen, Peigen
Li, Mengxiong
Fei, Hui
Huang, Jinfeng
Zhao, Tingting
Li, Tian
author_facet Liu, Yun
Chen, Peigen
Li, Mengxiong
Fei, Hui
Huang, Jinfeng
Zhao, Tingting
Li, Tian
author_sort Liu, Yun
collection PubMed
description 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.
format Online
Article
Text
id pubmed-8025127
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-80251272021-04-14 Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis Liu, Yun Chen, Peigen Li, Mengxiong Fei, Hui Huang, Jinfeng Zhao, Tingting Li, Tian Comput Math Methods Med Research Article 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. Hindawi 2021-03-29 /pmc/articles/PMC8025127/ /pubmed/33859719 http://dx.doi.org/10.1155/2021/6653295 Text en Copyright © 2021 Yun Liu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Yun
Chen, Peigen
Li, Mengxiong
Fei, Hui
Huang, Jinfeng
Zhao, Tingting
Li, Tian
Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis
title Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis
title_full Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis
title_fullStr Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis
title_full_unstemmed Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis
title_short Comprehensive Analysis of the Control of Cancer Stem Cell Characteristics in Endometrial Cancer by Network Analysis
title_sort comprehensive analysis of the control of cancer stem cell characteristics in endometrial cancer by network analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8025127/
https://www.ncbi.nlm.nih.gov/pubmed/33859719
http://dx.doi.org/10.1155/2021/6653295
work_keys_str_mv AT liuyun comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis
AT chenpeigen comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis
AT limengxiong comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis
AT feihui comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis
AT huangjinfeng comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis
AT zhaotingting comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis
AT litian comprehensiveanalysisofthecontrolofcancerstemcellcharacteristicsinendometrialcancerbynetworkanalysis