{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Lu D"],"funding":["Natural Science Foundation of Hubei Province","the PhD fellowship of Nanchang Hangkong University"],"pagination":["1749"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12480192"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["16(1)"],"pubmed_abstract":["<h4>Background</h4>The impact of tyrosine metabolism on the early diagnosis and treatment of breast cancer remains unclear. This underlines importance of exploring its mechanisms.<h4>Methods</h4>This study conducted an integrated analysis of breast cancer transcriptome data from the TCGA and GEO databases, utilizing differential expression analysis, enrichment analysis, immune infiltration analysis, single-cell RNA sequencing analysis, hdWGCNA analysis, and molecular docking to investigate the role of tyrosine metabolism in breast cancer and its relationship with chemotherapy response.<h4>Results</h4>The co-expression prognosis model of tyrosine metabolism developed in this study demonstrated superior performance in the prognostic assessment of breast cancer, achieving an AUC value of 0.73"],"journal":["Discover oncology"],"pubmed_title":["Deciphering key chemotherapeutic drug targets within tyrosine metabolism for breast cancer and advancing a wide-ranging diagnostic strategy."],"pmcid":["PMC12480192"],"funding_grant_id":["2019CFB391","EA202008259"],"pubmed_authors":["Shi HH","Yang J","Wu RM","Chen DJ","Lu D","Yi C","Cao SH","Jiang S","Xie ZL"],"additional_accession":[]},"is_claimable":false,"name":"Deciphering key chemotherapeutic drug targets within tyrosine metabolism for breast cancer and advancing a wide-ranging diagnostic strategy.","description":"<h4>Background</h4>The impact of tyrosine metabolism on the early diagnosis and treatment of breast cancer remains unclear. This underlines importance of exploring its mechanisms.<h4>Methods</h4>This study conducted an integrated analysis of breast cancer transcriptome data from the TCGA and GEO databases, utilizing differential expression analysis, enrichment analysis, immune infiltration analysis, single-cell RNA sequencing analysis, hdWGCNA analysis, and molecular docking to investigate the role of tyrosine metabolism in breast cancer and its relationship with chemotherapy response.<h4>Results</h4>The co-expression prognosis model of tyrosine metabolism developed in this study demonstrated superior performance in the prognostic assessment of breast cancer, achieving an AUC value of 0.73","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-07-15T09:48:06.721Z","creation":"2026-07-02T03:11:50.02Z"},"accession":"S-EPMC12480192","cross_references":{"pubmed":["41021173"],"doi":["10.1007/s12672-025-03577-x"]}}