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Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images

The purpose of this study was to use network pharmacology, biomedical images and molecular docking technology in the treatment of breast cancer to investigate the feasible therapeutic targets and mechanisms of trastuzumab. In the first place, we applied pubchem swisstarget (http://www.swisstargetpre...

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Autores principales: Lu, Yuan, Bi, Juan, Li, Fei, Wang, Gang, Zhu, Junjie, Jin, Jiqing, Liu, Yueyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304584/
https://www.ncbi.nlm.nih.gov/pubmed/35874525
http://dx.doi.org/10.3389/fphys.2022.942049
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author Lu, Yuan
Bi, Juan
Li, Fei
Wang, Gang
Zhu, Junjie
Jin, Jiqing
Liu, Yueyun
author_facet Lu, Yuan
Bi, Juan
Li, Fei
Wang, Gang
Zhu, Junjie
Jin, Jiqing
Liu, Yueyun
author_sort Lu, Yuan
collection PubMed
description The purpose of this study was to use network pharmacology, biomedical images and molecular docking technology in the treatment of breast cancer to investigate the feasible therapeutic targets and mechanisms of trastuzumab. In the first place, we applied pubchem swisstarget (http://www.swisstargetprediction.ch/), (https://pubchem.ncbi.nlm.nih.gov/) pharmmapper (http://lilab-ecust.cn/pharmmapper/), and the batman-tcm (http://bionet.ncpsb.org.cn/batman-tcm/) database to collect the trastuzumab targets. Then, in NCBI-GEO, breast cancer target genes were chosen (https://www.ncbi.nlm.nih.gov/geo/). The intersection regions of drug and disease target genes were used to draw a Venn diagram. Through Cytoscape 3.7.2 software, and the STRING database, we then formed a protein-protein interaction (PPI) network. Besides, we concluded KEGG pathway analysis and Geen Ontology analysis by using ClueGO in Cytospace. Finally, the top 5 target proteins in the PPI network to dock with trastuzumab were selected. After screening trastuzumab and breast cancer in databases separately, we got 521 target genes of the drug and 1,464 target genes of breast cancer. The number of overlapping genes was 54. PPI network core genes include GAPDH, MMP9, CCNA2, RRM2, CHEK1, etc. GO analysis indicated that trastuzumab treats breast cancer through abundant biological processes, especially positive regulation of phospholipase activity, linoleic acid metabolic process, and negative regulation of endothelial cell proliferation. The molecular function is NADP binding and the cellular component is tertiary granule lumen. The results of KEGG enrichment analysis exhibited four pathways related to the formation and cure of breast cancer, containing Drug metabolism, Glutathione metabolism, Pyrimidine metabolism and PPAR signaling pathway. Molecular docking showed that trastuzumab has good binding abilities with five core target proteins (GAPDH, MMP9, CCNA2, RRM2, CHEK1). This study, through network pharmacology and molecular docking, provides new pieces of evidence and ideas to understand how trastuzumab treats breast cancer at the gene level.
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spelling pubmed-93045842022-07-23 Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images Lu, Yuan Bi, Juan Li, Fei Wang, Gang Zhu, Junjie Jin, Jiqing Liu, Yueyun Front Physiol Physiology The purpose of this study was to use network pharmacology, biomedical images and molecular docking technology in the treatment of breast cancer to investigate the feasible therapeutic targets and mechanisms of trastuzumab. In the first place, we applied pubchem swisstarget (http://www.swisstargetprediction.ch/), (https://pubchem.ncbi.nlm.nih.gov/) pharmmapper (http://lilab-ecust.cn/pharmmapper/), and the batman-tcm (http://bionet.ncpsb.org.cn/batman-tcm/) database to collect the trastuzumab targets. Then, in NCBI-GEO, breast cancer target genes were chosen (https://www.ncbi.nlm.nih.gov/geo/). The intersection regions of drug and disease target genes were used to draw a Venn diagram. Through Cytoscape 3.7.2 software, and the STRING database, we then formed a protein-protein interaction (PPI) network. Besides, we concluded KEGG pathway analysis and Geen Ontology analysis by using ClueGO in Cytospace. Finally, the top 5 target proteins in the PPI network to dock with trastuzumab were selected. After screening trastuzumab and breast cancer in databases separately, we got 521 target genes of the drug and 1,464 target genes of breast cancer. The number of overlapping genes was 54. PPI network core genes include GAPDH, MMP9, CCNA2, RRM2, CHEK1, etc. GO analysis indicated that trastuzumab treats breast cancer through abundant biological processes, especially positive regulation of phospholipase activity, linoleic acid metabolic process, and negative regulation of endothelial cell proliferation. The molecular function is NADP binding and the cellular component is tertiary granule lumen. The results of KEGG enrichment analysis exhibited four pathways related to the formation and cure of breast cancer, containing Drug metabolism, Glutathione metabolism, Pyrimidine metabolism and PPAR signaling pathway. Molecular docking showed that trastuzumab has good binding abilities with five core target proteins (GAPDH, MMP9, CCNA2, RRM2, CHEK1). This study, through network pharmacology and molecular docking, provides new pieces of evidence and ideas to understand how trastuzumab treats breast cancer at the gene level. Frontiers Media S.A. 2022-07-08 /pmc/articles/PMC9304584/ /pubmed/35874525 http://dx.doi.org/10.3389/fphys.2022.942049 Text en Copyright © 2022 Lu, Bi, Li, Wang, Zhu, Jin and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Lu, Yuan
Bi, Juan
Li, Fei
Wang, Gang
Zhu, Junjie
Jin, Jiqing
Liu, Yueyun
Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images
title Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images
title_full Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images
title_fullStr Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images
title_full_unstemmed Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images
title_short Differential Gene Analysis of Trastuzumab in Breast Cancer Based on Network Pharmacology and Medical Images
title_sort differential gene analysis of trastuzumab in breast cancer based on network pharmacology and medical images
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9304584/
https://www.ncbi.nlm.nih.gov/pubmed/35874525
http://dx.doi.org/10.3389/fphys.2022.942049
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