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Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer

Breast cancer is the most prevalent malignancy among females, but the molecular mechanisms involved in its pathogenesis and progression have remained to be fully elucidated. The aim of the present study was to identify novel potential therapeutic targets for breast cancer. The dataset GSE76275 was d...

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Autores principales: Yang, Lijie, Li, Xuanfei, Luo, Yixing, Yang, Tiecheng, Wang, Huaqiao, Shi, Liwen, Feng, Maohui, Xie, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8343771/
https://www.ncbi.nlm.nih.gov/pubmed/34373716
http://dx.doi.org/10.3892/etm.2021.10462
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author Yang, Lijie
Li, Xuanfei
Luo, Yixing
Yang, Tiecheng
Wang, Huaqiao
Shi, Liwen
Feng, Maohui
Xie, Wei
author_facet Yang, Lijie
Li, Xuanfei
Luo, Yixing
Yang, Tiecheng
Wang, Huaqiao
Shi, Liwen
Feng, Maohui
Xie, Wei
author_sort Yang, Lijie
collection PubMed
description Breast cancer is the most prevalent malignancy among females, but the molecular mechanisms involved in its pathogenesis and progression have remained to be fully elucidated. The aim of the present study was to identify novel potential therapeutic targets for breast cancer. The dataset GSE76275 was downloaded from the Gene Expression Omnibus database and weighted gene co-expression network analysis (WGCNA) was performed to identify hub genes. Furthermore, the dataset GSE25055, containing gene expression data and clinical information, was downloaded to validate the expression and survival association of these hub genes. In addition, the datasets GSE25065 and GSE42568 were used to validate the association between hub gene expression levels and clinical features. Immunohistochemistry (IHC), reverse transcription-quantitative PCR, as well as proliferation, migration, invasion and apoptosis assays, were used to verify gene expression and function. A total of 4,052 genes were selected for WGCNA and 18 modules were established; the red module was identified as the key module, as it had a strong positive correlation with the tumor grade. Survival analyses of hub genes [S-adenosylmethionine decarboxylase proenzyme (AMD1), homeobox protein engrailed-1 (EN1) and vestigial-like protein (VGLL1)] indicated that higher levels of gene expression were associated with poor prognosis of patients with breast cancer. This association was based on survival analysis of GSE25055 using the Kaplan-Meier plotter tool. Expression validation revealed that the upregulation of hub genes was associated with advanced tumor grade and malignant molecular subtype (basal-like). IHC results from the Human Protein Atlas also demonstrated that protein expression levels of the hub genes were higher in tumor tissues compared with those in adjacent normal tissues. Furthermore, the expression levels of AMD1, EN1 and VGLL1 were strongly correlated with each other. These results demonstrated that AMD1 is highly expressed in breast cancer tissues and cells and AMD1 knockdown decreased the proliferation and metastatic potential, while increasing apoptosis of breast cancer cells. These results suggested that AMD1, EN1 and VGLL1 are likely to contribute to breast cancer progression and unfavorable prognosis.
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spelling pubmed-83437712021-08-08 Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer Yang, Lijie Li, Xuanfei Luo, Yixing Yang, Tiecheng Wang, Huaqiao Shi, Liwen Feng, Maohui Xie, Wei Exp Ther Med Articles Breast cancer is the most prevalent malignancy among females, but the molecular mechanisms involved in its pathogenesis and progression have remained to be fully elucidated. The aim of the present study was to identify novel potential therapeutic targets for breast cancer. The dataset GSE76275 was downloaded from the Gene Expression Omnibus database and weighted gene co-expression network analysis (WGCNA) was performed to identify hub genes. Furthermore, the dataset GSE25055, containing gene expression data and clinical information, was downloaded to validate the expression and survival association of these hub genes. In addition, the datasets GSE25065 and GSE42568 were used to validate the association between hub gene expression levels and clinical features. Immunohistochemistry (IHC), reverse transcription-quantitative PCR, as well as proliferation, migration, invasion and apoptosis assays, were used to verify gene expression and function. A total of 4,052 genes were selected for WGCNA and 18 modules were established; the red module was identified as the key module, as it had a strong positive correlation with the tumor grade. Survival analyses of hub genes [S-adenosylmethionine decarboxylase proenzyme (AMD1), homeobox protein engrailed-1 (EN1) and vestigial-like protein (VGLL1)] indicated that higher levels of gene expression were associated with poor prognosis of patients with breast cancer. This association was based on survival analysis of GSE25055 using the Kaplan-Meier plotter tool. Expression validation revealed that the upregulation of hub genes was associated with advanced tumor grade and malignant molecular subtype (basal-like). IHC results from the Human Protein Atlas also demonstrated that protein expression levels of the hub genes were higher in tumor tissues compared with those in adjacent normal tissues. Furthermore, the expression levels of AMD1, EN1 and VGLL1 were strongly correlated with each other. These results demonstrated that AMD1 is highly expressed in breast cancer tissues and cells and AMD1 knockdown decreased the proliferation and metastatic potential, while increasing apoptosis of breast cancer cells. These results suggested that AMD1, EN1 and VGLL1 are likely to contribute to breast cancer progression and unfavorable prognosis. D.A. Spandidos 2021-09 2021-07-18 /pmc/articles/PMC8343771/ /pubmed/34373716 http://dx.doi.org/10.3892/etm.2021.10462 Text en Copyright: © Yang et al. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Yang, Lijie
Li, Xuanfei
Luo, Yixing
Yang, Tiecheng
Wang, Huaqiao
Shi, Liwen
Feng, Maohui
Xie, Wei
Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer
title Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer
title_full Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer
title_fullStr Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer
title_full_unstemmed Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer
title_short Weighted gene co-expression network analysis of the association between upregulated AMD1, EN1 and VGLL1 and the progression and poor prognosis of breast cancer
title_sort weighted gene co-expression network analysis of the association between upregulated amd1, en1 and vgll1 and the progression and poor prognosis of breast cancer
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8343771/
https://www.ncbi.nlm.nih.gov/pubmed/34373716
http://dx.doi.org/10.3892/etm.2021.10462
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