Article ; Online: Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer.
Journal of immunology research
2022 Volume 2022, Page(s) 9529114
Abstract: Objective: To identify trastuzumab-resistant genes predicting drug response and poor prognosis in human epidermal growth factor receptor 2 positive (HER2+) breast cancer.: Methods: Gene expression profiles from the GEO (Gene Expression Omnibus) ... ...
Abstract | Objective: To identify trastuzumab-resistant genes predicting drug response and poor prognosis in human epidermal growth factor receptor 2 positive (HER2+) breast cancer. Methods: Gene expression profiles from the GEO (Gene Expression Omnibus) database were obtained and analyzed. Differentially expressed genes (DEGs) between the pathological complete response (pCR) group and non-pCR group in a trastuzumab neoadjuvant therapy cohort and DEGs between Herceptin-resistant and wild-type cell lines were detected and evaluated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were performed to select the functional hub genes. The hub genes' prognostic power was validated by another trastuzumab adjuvant treatment cohort. Results: Fifty upregulated overlapping DEGs were identified by analyzing two trastuzumab resistance-related GEO databases. Functional analysis picked out ten hub genes enriched in mitochondrial function and metabolism pathways: Conclusion: Ten novel trastuzumab resistance-related genes were discovered, of which |
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MeSH term(s) | Breast Neoplasms/drug therapy ; Breast Neoplasms/genetics ; Breast Neoplasms/metabolism ; Female ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; Receptor, ErbB-2 ; Trastuzumab/pharmacology ; Trastuzumab/therapeutic use |
Chemical Substances | ERBB2 protein, human (EC 2.7.10.1) ; Receptor, ErbB-2 (EC 2.7.10.1) ; Trastuzumab (P188ANX8CK) |
Language | English |
Publishing date | 2022-07-27 |
Publishing country | Egypt |
Document type | Journal Article |
ZDB-ID | 2817541-4 |
ISSN | 2314-7156 ; 2314-7156 |
ISSN (online) | 2314-7156 |
ISSN | 2314-7156 |
DOI | 10.1155/2022/9529114 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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