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Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools

Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as poten...

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Autor principal: Oumeddour, Abdelkader
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019133/
https://www.ncbi.nlm.nih.gov/pubmed/36930083
http://dx.doi.org/10.1097/MD.0000000000033291
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author Oumeddour, Abdelkader
author_facet Oumeddour, Abdelkader
author_sort Oumeddour, Abdelkader
collection PubMed
description Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan–Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4(+) T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment.
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spelling pubmed-100191332023-03-17 Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools Oumeddour, Abdelkader Medicine (Baltimore) 5750 Breast cancer (BC) remains the leading cause of cancer-related death in women worldwide. The development of new targeted therapies that may improve patient survival remains an area of growing interest. This study aimed to identify new biomarkers involved in BC progression that could be used as potential targeted therapies. DEGs were selected from three gene expression profiles, GSE55715, GSE124646, and GSE87049, using the GEO2R tool and Venn diagram software. Gene Ontology and KEGG pathways were then performed using DAVID software. Next, the PPI network was constructed using STRING and visualized using Cytoscape software, and hub genes were extracted using the cytoHubba plug-in. Survival analysis was performed using the Kaplan–Meier Plotter, while the expression of hub genes in BC was verified using the GEPIA2 tool. Finally, transcription the factors of hub genes were determined using the NetworkAnalyst database, and the TIMER tool was employed to explore the infiltration levels of tumor immune cells with related genes. A total of 146 DEGs were identified in the three datasets, including 60 upregulated genes that were enriched in the cell cycle, and 86 downregulated genes that were mainly enriched in the TNF signaling pathway and pathways in cancer. Ten genes were identified: BUB1, CDK1, HMMR, MAD2L1, CEP55, AURKA, CCNB2, TPX2, MELK, and KIF20A. The overexpression of hub genes, except CDK1, was associated with poor survival in BC and was regulated by several transcription factors involved in DNA binding activity and transcription regulation. The infiltration levels of immune cells were positively correlated with hub genes, particularly macrophages and CD4(+) T cells. This study identified new reliable molecular biomarkers that can serve as potential therapeutic targets for BC treatment. Lippincott Williams & Wilkins 2023-03-17 /pmc/articles/PMC10019133/ /pubmed/36930083 http://dx.doi.org/10.1097/MD.0000000000033291 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 5750
Oumeddour, Abdelkader
Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
title Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
title_full Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
title_fullStr Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
title_full_unstemmed Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
title_short Screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
title_sort screening of potential hub genes and key pathways associated with breast cancer by bioinformatics tools
topic 5750
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019133/
https://www.ncbi.nlm.nih.gov/pubmed/36930083
http://dx.doi.org/10.1097/MD.0000000000033291
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