Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis

Abstract Background With the gradual unveiling of tumour heterogeneity, cancer stem cells (CSCs) are now being considered the initial component of tumour initiation. However, the mechanisms of the growth and maintenance of breast cancer (BRCA) stem cells are still unknown. Methods To explore the cru...

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Main Authors: Jianying Pei, Yanxia Wang, Yan Li
Format: Article
Language:English
Published: BMC 2020-02-01
Series:Journal of Translational Medicine
Subjects:
Online Access:https://doi.org/10.1186/s12967-020-02260-9
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spelling doaj-29c8dd00c36f40538935a4768dd87e7b2021-02-14T12:10:28ZengBMCJournal of Translational Medicine1479-58762020-02-0118111510.1186/s12967-020-02260-9Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysisJianying Pei0Yanxia Wang1Yan Li2Gansu Provincial Maternity and Child-care HospitalGansu Provincial Maternity and Child-care HospitalGansu Province Key Laboratory of Biotherapy and Regenerative Medicine, the First Hospital of Lanzhou UniversityAbstract Background With the gradual unveiling of tumour heterogeneity, cancer stem cells (CSCs) are now being considered the initial component of tumour initiation. However, the mechanisms of the growth and maintenance of breast cancer (BRCA) stem cells are still unknown. Methods To explore the crucial genes modulating BRCA stemness characteristics, we combined the gene expression value and mRNA expression-based stemness index (mRNAsi) of samples from The Cancer Genome Atlas (TCGA), and the mRNAsi was corrected using the tumour purity (corrected mRNAsi). mRNAsi and corrected mRNAsi were analysed and showed a close relationship with BRCA clinical characteristics, including tumour depth, pathological staging and survival status. Next, weighted gene co-expression network analysis (WGCNA) was applied to distinguish crucial gene modules and key genes. A series of functional analyses and expression validation of key genes were conducted using multiple databases, including Oncomine, Gene Expression Omnibus (GEO) and Gene Expression Profiling Integrative Analysis (GEPIA). Results This study found that mRNAsi and corrected mRNAsi scores were higher in BRCA tissues than that in normal tissues, and both of them increased with tumour stage. Higher corrected mRNAsi scores showed worse overall survival outcomes. We screened 3 modules and 32 key genes, and those key genes were found to be strongly correlated with each other. Functional analysis revealed that the key genes were related to cell fate decision events such as the cell cycle, cellular senescence, chromosome segregation and mitotic nuclear division. Among 32 key genes, we identified 12 genes that strongly correlated with BRCA survival. Conclusions Thirty-two genes were found to be closely related to BRCA stem cell characteristics; among them, 12 genes showed prognosis-oriented effects in BRCA patients. The most significant signalling pathway related to stemness in BRCA was the cell cycle pathway, which may support new ideas for screening therapeutic targets to inhibit BRCA stem characteristics. These findings may highlight some therapeutic targets for inhibiting BRCA stem cells.https://doi.org/10.1186/s12967-020-02260-9Breast cancerCancer cell stemnessmRNAsiWGCNA
collection DOAJ
language English
format Article
sources DOAJ
author Jianying Pei
Yanxia Wang
Yan Li
spellingShingle Jianying Pei
Yanxia Wang
Yan Li
Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
Journal of Translational Medicine
Breast cancer
Cancer cell stemness
mRNAsi
WGCNA
author_facet Jianying Pei
Yanxia Wang
Yan Li
author_sort Jianying Pei
title Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
title_short Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
title_full Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
title_fullStr Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
title_full_unstemmed Identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
title_sort identification of key genes controlling breast cancer stem cell characteristics via stemness indices analysis
publisher BMC
series Journal of Translational Medicine
issn 1479-5876
publishDate 2020-02-01
description Abstract Background With the gradual unveiling of tumour heterogeneity, cancer stem cells (CSCs) are now being considered the initial component of tumour initiation. However, the mechanisms of the growth and maintenance of breast cancer (BRCA) stem cells are still unknown. Methods To explore the crucial genes modulating BRCA stemness characteristics, we combined the gene expression value and mRNA expression-based stemness index (mRNAsi) of samples from The Cancer Genome Atlas (TCGA), and the mRNAsi was corrected using the tumour purity (corrected mRNAsi). mRNAsi and corrected mRNAsi were analysed and showed a close relationship with BRCA clinical characteristics, including tumour depth, pathological staging and survival status. Next, weighted gene co-expression network analysis (WGCNA) was applied to distinguish crucial gene modules and key genes. A series of functional analyses and expression validation of key genes were conducted using multiple databases, including Oncomine, Gene Expression Omnibus (GEO) and Gene Expression Profiling Integrative Analysis (GEPIA). Results This study found that mRNAsi and corrected mRNAsi scores were higher in BRCA tissues than that in normal tissues, and both of them increased with tumour stage. Higher corrected mRNAsi scores showed worse overall survival outcomes. We screened 3 modules and 32 key genes, and those key genes were found to be strongly correlated with each other. Functional analysis revealed that the key genes were related to cell fate decision events such as the cell cycle, cellular senescence, chromosome segregation and mitotic nuclear division. Among 32 key genes, we identified 12 genes that strongly correlated with BRCA survival. Conclusions Thirty-two genes were found to be closely related to BRCA stem cell characteristics; among them, 12 genes showed prognosis-oriented effects in BRCA patients. The most significant signalling pathway related to stemness in BRCA was the cell cycle pathway, which may support new ideas for screening therapeutic targets to inhibit BRCA stem characteristics. These findings may highlight some therapeutic targets for inhibiting BRCA stem cells.
topic Breast cancer
Cancer cell stemness
mRNAsi
WGCNA
url https://doi.org/10.1186/s12967-020-02260-9
work_keys_str_mv AT jianyingpei identificationofkeygenescontrollingbreastcancerstemcellcharacteristicsviastemnessindicesanalysis
AT yanxiawang identificationofkeygenescontrollingbreastcancerstemcellcharacteristicsviastemnessindicesanalysis
AT yanli identificationofkeygenescontrollingbreastcancerstemcellcharacteristicsviastemnessindicesanalysis
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