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Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation

Background: Paeoniflorin (PF) is the main active component of Chinese herbaceous peony that has been shown to have an anti-tumor effect. However, there are few studies on the prevention and treatment of pancreatic cancer with PF. Methods: We gathered Microarray data pertaining to paeoniflorin interv...

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Autores principales: Cao, Chunhao, Zhao, Wenting, Chen, Xianglin, Shen, Bin, Wang, Teng, Wu, Chaoxu, Rong, Xiaofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630940/
https://www.ncbi.nlm.nih.gov/pubmed/36339551
http://dx.doi.org/10.3389/fphar.2022.1032282
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author Cao, Chunhao
Zhao, Wenting
Chen, Xianglin
Shen, Bin
Wang, Teng
Wu, Chaoxu
Rong, Xiaofeng
author_facet Cao, Chunhao
Zhao, Wenting
Chen, Xianglin
Shen, Bin
Wang, Teng
Wu, Chaoxu
Rong, Xiaofeng
author_sort Cao, Chunhao
collection PubMed
description Background: Paeoniflorin (PF) is the main active component of Chinese herbaceous peony that has been shown to have an anti-tumor effect. However, there are few studies on the prevention and treatment of pancreatic cancer with PF. Methods: We gathered Microarray data pertaining to paeoniflorin intervention in pancreatic cancer by utilizing the GEO database (GSE97124). Then, the DEGs were filtered by the 33R program. RNA-seq data of pancreatic cancer and normal tissue samples were taken from the TCGA and GTEx databases, respectively, and the WGCNA technique was utilized to examine the pancreatic cancer-specific genes. Paeoniflorin target genes for the treatment of pancreatic cancer were determined based on the overlap between DEGs and WGCNA. GO and KEGG enrichment analyses were then performed on paeoniflorin target genes to discover which biological processes were impacted. Using the 3 hierarchical methods included in the Cytohubba plugin, we re-screened the hub genes in the target genes to find the genes most relevant to paeoniflorin treatment. The overall survival effects of hub genes were confirmed using the TCGA database. Finally, the paeoniflorin targets identified by the network pharmacology analysis were validated using PANC-1 and Capan-2 cells. Results: We identified 148 main potential PF targets, and gene enrichment analysis suggested that the aforementioned targets play a crucial role in the regulation of MAPK, PI3K-AKT, and other pathways. The further screening of the prospective targets resulted in the identification of 39 hub genes. Using the TCGA database, it was determined that around 33.33% of the hub gene’s high expression was linked with a bad prognosis. Finally, we demonstrated that PF inhibits IL-6 and IL-10 expression and p38 phosphorylation in pancreatic cancer cells, thereby reducing inflammation. Conclusion: PF may regulate inflammatory factors mainly through the p38 MAPK signal pathway. These findings provide theoretical and experimental evidence suggesting the PF as a promising natural source of anti-tumor compounds for pancreatic cancer.
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spelling pubmed-96309402022-11-04 Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation Cao, Chunhao Zhao, Wenting Chen, Xianglin Shen, Bin Wang, Teng Wu, Chaoxu Rong, Xiaofeng Front Pharmacol Pharmacology Background: Paeoniflorin (PF) is the main active component of Chinese herbaceous peony that has been shown to have an anti-tumor effect. However, there are few studies on the prevention and treatment of pancreatic cancer with PF. Methods: We gathered Microarray data pertaining to paeoniflorin intervention in pancreatic cancer by utilizing the GEO database (GSE97124). Then, the DEGs were filtered by the 33R program. RNA-seq data of pancreatic cancer and normal tissue samples were taken from the TCGA and GTEx databases, respectively, and the WGCNA technique was utilized to examine the pancreatic cancer-specific genes. Paeoniflorin target genes for the treatment of pancreatic cancer were determined based on the overlap between DEGs and WGCNA. GO and KEGG enrichment analyses were then performed on paeoniflorin target genes to discover which biological processes were impacted. Using the 3 hierarchical methods included in the Cytohubba plugin, we re-screened the hub genes in the target genes to find the genes most relevant to paeoniflorin treatment. The overall survival effects of hub genes were confirmed using the TCGA database. Finally, the paeoniflorin targets identified by the network pharmacology analysis were validated using PANC-1 and Capan-2 cells. Results: We identified 148 main potential PF targets, and gene enrichment analysis suggested that the aforementioned targets play a crucial role in the regulation of MAPK, PI3K-AKT, and other pathways. The further screening of the prospective targets resulted in the identification of 39 hub genes. Using the TCGA database, it was determined that around 33.33% of the hub gene’s high expression was linked with a bad prognosis. Finally, we demonstrated that PF inhibits IL-6 and IL-10 expression and p38 phosphorylation in pancreatic cancer cells, thereby reducing inflammation. Conclusion: PF may regulate inflammatory factors mainly through the p38 MAPK signal pathway. These findings provide theoretical and experimental evidence suggesting the PF as a promising natural source of anti-tumor compounds for pancreatic cancer. Frontiers Media S.A. 2022-10-20 /pmc/articles/PMC9630940/ /pubmed/36339551 http://dx.doi.org/10.3389/fphar.2022.1032282 Text en Copyright © 2022 Cao, Zhao, Chen, Shen, Wang, Wu and Rong. 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 Pharmacology
Cao, Chunhao
Zhao, Wenting
Chen, Xianglin
Shen, Bin
Wang, Teng
Wu, Chaoxu
Rong, Xiaofeng
Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation
title Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation
title_full Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation
title_fullStr Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation
title_full_unstemmed Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation
title_short Deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: A network pharmacology study and experimental validation
title_sort deciphering the action mechanism of paeoniflorin in suppressing pancreatic cancer: a network pharmacology study and experimental validation
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9630940/
https://www.ncbi.nlm.nih.gov/pubmed/36339551
http://dx.doi.org/10.3389/fphar.2022.1032282
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