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Identification of genes and pathways associated with menopausal status in breast cancer patients using two algorithms.
Cheng, Minzhang; Wang, Lingchen; Xuan, Yanlu; Zhai, Zhenyu.
Affiliation
  • Cheng M; Jiangxi Clinical Research Center for Respiratory Diseases, Jiangxi Institute of Respiratory Disease, the Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China.
  • Wang L; Jiangxi Key Laboratory of Molecular Diagnostics and Precision Medicine, Center for Experimental Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China.
  • Xuan Y; School of Public Health, University of Nevada, Reno, Reno, Nevada, 89557, USA.
  • Zhai Z; Jiangxi Clinical Research Center for Respiratory Diseases, Jiangxi Institute of Respiratory Disease, the Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330006, China.
BMC Womens Health ; 24(1): 4, 2024 01 02.
Article de En | MEDLINE | ID: mdl-38166892
ABSTRACT

BACKGROUND:

Menopausal status has a known relationship with the levels of estrogen, progesterone, and other sex hormones, potentially influencing the activity of ER, PR, and many other signaling pathways involved in the initiation and progression of breast cancer. However, the differences between premenopausal and postmenopausal breast cancer patients at the molecular level are unclear.

METHODS:

We retrieved eight datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) associated with menopausal status in breast cancer patients were identified using the MAMA and LIMMA methods. Based on these validated DEGs, we performed Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) networks were constructed. We used DrugBank data to investigate which of these validated DEGs are targetable. Survival analysis was performed to explore the influence of these genes on breast cancer patient prognosis.

RESULTS:

We identified 762 DEGs associated with menopausal status in breast cancer patients. PPI network analysis indicated that these genes are primarily involved in pathways such as the cell cycle, oocyte meiosis and progesterone-mediated oocyte maturation pathways. Notably, several genes played roles in multiple signaling pathways and were associated with patient survival. These genes were also observed to be targetable according to the DrugBank database.

CONCLUSION:

We identified DEGs associated with menopausal status in breast cancer patients. The association of these genes with several key pathways may promote understanding of the complex characterizations of breast cancer. Our findings offer valuable insights for developing new therapeutic strategies tailored to the menopausal status of breast cancer patients.
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Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tumeurs du sein / Ménopause Type d'étude: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limites: Female / Humans Langue: En Journal: BMC Womens Health Sujet du journal: SAUDE DA MULHER Année: 2024 Type de document: Article Pays d'affiliation: Chine Pays de publication: Royaume-Uni

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Tumeurs du sein / Ménopause Type d'étude: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limites: Female / Humans Langue: En Journal: BMC Womens Health Sujet du journal: SAUDE DA MULHER Année: 2024 Type de document: Article Pays d'affiliation: Chine Pays de publication: Royaume-Uni