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Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma

BACKGROUND: An anti-tumour activity has been demonstrated for α-solanine, a bioactive compound extracted from the traditional Chinese herb Solanum nigrum L. However, its efficacy in the treatment of gliomas and the underlying mechanisms remain unclear. The aim of this study was to investigate the in...

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Autores principales: Wang, ChunPeng, Liu, XiaoHui, Guo, ShiWen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589944/
https://www.ncbi.nlm.nih.gov/pubmed/37865727
http://dx.doi.org/10.1186/s12906-023-04215-1
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author Wang, ChunPeng
Liu, XiaoHui
Guo, ShiWen
author_facet Wang, ChunPeng
Liu, XiaoHui
Guo, ShiWen
author_sort Wang, ChunPeng
collection PubMed
description BACKGROUND: An anti-tumour activity has been demonstrated for α-solanine, a bioactive compound extracted from the traditional Chinese herb Solanum nigrum L. However, its efficacy in the treatment of gliomas and the underlying mechanisms remain unclear. The aim of this study was to investigate the inhibitory effects of α-solanine on glioma and elucidate its mechanisms and targets using network pharmacology, molecular docking, and molecular biology experiments. METHODS: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to predict the potential targets of α-solanine. GeneCards was used to gather glioma-related targets, and the STRING online database was used to analyze protein–protein interaction (PPI) networks for the shared targets. Hub genes were identified from the resulting PPI network and further investigated using Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Additionally, prognostic and gene set enrichment analyses (GSEA) were carried out to identify potential therapeutic targets and their underlying mechanisms of action in relation to the prognosis of gliomas. In vitro experiments were conducted to verify the findings from the network pharmacology analysis. RESULTS: A total of 289 α-solanine targets and 1149 glioma-related targets were screened, of which 78 were common targets. 11 hub genes were obtained, including SRC, HRAS, HSP90AA1, IGF1, MAPK1, MAPK14, KDR, STAT1, JAK2, MAP2K1, and IGF1R. The GO and KEGG pathway analyses unveiled that α-solanine was strongly associated with several signaling pathways, including positive regulation of MAP kinase activity and PI3K-Akt. Moreover, α-solanine (10 µM and 15 µM) inhibited the proliferation and migration but promoted the apoptosis of glioma cells. Finally, STAT1 was identified as a potential mediator of the effect of α-solanine on glioma prognosis. CONCLUSION: α-Solanine can inhibit the proliferation and migration of gliomas by regulating multiple targets and signalling pathways. These findings lay the foundation for the creation of innovative clinical anti-glioma agents. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12906-023-04215-1.
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spelling pubmed-105899442023-10-22 Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma Wang, ChunPeng Liu, XiaoHui Guo, ShiWen BMC Complement Med Ther Research BACKGROUND: An anti-tumour activity has been demonstrated for α-solanine, a bioactive compound extracted from the traditional Chinese herb Solanum nigrum L. However, its efficacy in the treatment of gliomas and the underlying mechanisms remain unclear. The aim of this study was to investigate the inhibitory effects of α-solanine on glioma and elucidate its mechanisms and targets using network pharmacology, molecular docking, and molecular biology experiments. METHODS: Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to predict the potential targets of α-solanine. GeneCards was used to gather glioma-related targets, and the STRING online database was used to analyze protein–protein interaction (PPI) networks for the shared targets. Hub genes were identified from the resulting PPI network and further investigated using Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Additionally, prognostic and gene set enrichment analyses (GSEA) were carried out to identify potential therapeutic targets and their underlying mechanisms of action in relation to the prognosis of gliomas. In vitro experiments were conducted to verify the findings from the network pharmacology analysis. RESULTS: A total of 289 α-solanine targets and 1149 glioma-related targets were screened, of which 78 were common targets. 11 hub genes were obtained, including SRC, HRAS, HSP90AA1, IGF1, MAPK1, MAPK14, KDR, STAT1, JAK2, MAP2K1, and IGF1R. The GO and KEGG pathway analyses unveiled that α-solanine was strongly associated with several signaling pathways, including positive regulation of MAP kinase activity and PI3K-Akt. Moreover, α-solanine (10 µM and 15 µM) inhibited the proliferation and migration but promoted the apoptosis of glioma cells. Finally, STAT1 was identified as a potential mediator of the effect of α-solanine on glioma prognosis. CONCLUSION: α-Solanine can inhibit the proliferation and migration of gliomas by regulating multiple targets and signalling pathways. These findings lay the foundation for the creation of innovative clinical anti-glioma agents. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12906-023-04215-1. BioMed Central 2023-10-21 /pmc/articles/PMC10589944/ /pubmed/37865727 http://dx.doi.org/10.1186/s12906-023-04215-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Wang, ChunPeng
Liu, XiaoHui
Guo, ShiWen
Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
title Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
title_full Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
title_fullStr Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
title_full_unstemmed Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
title_short Network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
title_sort network pharmacology-based strategy to investigate the effect and mechanism of α-solanine against glioma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589944/
https://www.ncbi.nlm.nih.gov/pubmed/37865727
http://dx.doi.org/10.1186/s12906-023-04215-1
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