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Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer

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 expr...

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Autores principales: Dong, Xinrui, Dai, Huijuan, Sun, Aijun, Yu, Zhenfeng, Du, Yueyao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348965/
https://www.ncbi.nlm.nih.gov/pubmed/35935587
http://dx.doi.org/10.1155/2022/9529114
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author Dong, Xinrui
Dai, Huijuan
Sun, Aijun
Yu, Zhenfeng
Du, Yueyao
author_facet Dong, Xinrui
Dai, Huijuan
Sun, Aijun
Yu, Zhenfeng
Du, Yueyao
author_sort Dong, Xinrui
collection PubMed
description 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: ASCL1, CPT2, DLD, ELVOL7, GAMT, NQO1, SLC23A1, SPR, UQCRB, and UQCRQ. These hub genes could distinguish patients with trastuzumab resistance from the sensitive ones. Further survival analysis of hub genes showed that DLD overexpression was significantly associated with an unfavorable prognosis in HER2+ breast cancer patients. CONCLUSION: Ten novel trastuzumab resistance-related genes were discovered, of which DLD could be used for trastuzumab response prediction and prognostic prediction in HER2+ breast cancer.
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spelling pubmed-93489652022-08-04 Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer Dong, Xinrui Dai, Huijuan Sun, Aijun Yu, Zhenfeng Du, Yueyao J Immunol Res Research Article 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: ASCL1, CPT2, DLD, ELVOL7, GAMT, NQO1, SLC23A1, SPR, UQCRB, and UQCRQ. These hub genes could distinguish patients with trastuzumab resistance from the sensitive ones. Further survival analysis of hub genes showed that DLD overexpression was significantly associated with an unfavorable prognosis in HER2+ breast cancer patients. CONCLUSION: Ten novel trastuzumab resistance-related genes were discovered, of which DLD could be used for trastuzumab response prediction and prognostic prediction in HER2+ breast cancer. Hindawi 2022-07-27 /pmc/articles/PMC9348965/ /pubmed/35935587 http://dx.doi.org/10.1155/2022/9529114 Text en Copyright © 2022 Xinrui Dong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Dong, Xinrui
Dai, Huijuan
Sun, Aijun
Yu, Zhenfeng
Du, Yueyao
Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer
title Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer
title_full Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer
title_fullStr Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer
title_full_unstemmed Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer
title_short Identification of Genes Predicting Poor Response of Trastuzumab in Human Epidermal Growth Factor Receptor 2 Positive Breast Cancer
title_sort identification of genes predicting poor response of trastuzumab in human epidermal growth factor receptor 2 positive breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9348965/
https://www.ncbi.nlm.nih.gov/pubmed/35935587
http://dx.doi.org/10.1155/2022/9529114
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