Novel systems biology experimental pipeline reveals matairesinol’s antimetastatic potential in prostate cancer: an integrated approach of network pharmacology, bioinformatics, and experimental validation
{"title":"Novel systems biology experimental pipeline reveals matairesinol’s antimetastatic potential in prostate cancer: an integrated approach of network pharmacology, bioinformatics, and experimental validation","authors":"Rama Rajadnya, Nidhi Sharma, Akanksha Mahajan, Amrita Ulhe, Rajesh Patil, Mahabaleshwar Hegde, Aniket Mali","doi":"10.1093/bib/bbae466","DOIUrl":null,"url":null,"abstract":"Matairesinol (MAT), a plant lignan renowned for its anticancer properties in hormone-sensitive cancers like breast and prostate cancers, presents a promising yet underexplored avenue in the treatment of metastatic prostate cancer (mPC). To elucidate its specific therapeutic targets and mechanisms, our study adopted an integrative approach, amalgamating network pharmacology (NP), bioinformatics, GeneMANIA-based functional association (GMFA), and experimental validation. By mining online databases, we identified 27 common targets of mPC and MAT, constructing a MAT-mPC protein–protein interaction network via STRING and pinpointing 11 hub targets such as EGFR, AKT1, ERBB2, MET, IGF1, CASP3, HSP90AA1, HIF1A, MMP2, HGF, and MMP9 with CytoHuba. Utilizing DAVID, Gene Ontology (GO) analysis highlighted metastasis-related processes such as epithelial–mesenchymal transition, positive regulation of cell migration, and key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cancer, prostate cancer, PI3K-Akt, and MAPK signaling, while the web resources such as UALCAN and GEPIA2 affirmed the clinical significance of the top 11 hub targets in mPC patient survival analysis and gene expression patterns. Our innovative GMFA enrichment method further enriched network pharmacology findings. Molecular docking analyses demonstrated substantial interactions between MAT and 11 hub targets. Simulation studies confirmed the stable interactions of MAT with selected targets. Experimental validation in PC3 cells, employing quantitative real-time reverse-transcription PCR and various cell-based assays, corroborated MAT’s antimetastatic effects on mPC. Thus, this exhaustive NP analysis, complemented by GMFA, molecular docking, molecular dynamics simulations, and experimental validations, underscores MAT’s multifaceted role in targeting mPC through diverse therapeutic avenues. Nevertheless, comprehensive in vitro validation is imperative to solidify these findings.","PeriodicalId":9209,"journal":{"name":"Briefings in bioinformatics","volume":"25 1","pages":""},"PeriodicalIF":6.8000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Briefings in bioinformatics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/bib/bbae466","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Matairesinol (MAT), a plant lignan renowned for its anticancer properties in hormone-sensitive cancers like breast and prostate cancers, presents a promising yet underexplored avenue in the treatment of metastatic prostate cancer (mPC). To elucidate its specific therapeutic targets and mechanisms, our study adopted an integrative approach, amalgamating network pharmacology (NP), bioinformatics, GeneMANIA-based functional association (GMFA), and experimental validation. By mining online databases, we identified 27 common targets of mPC and MAT, constructing a MAT-mPC protein–protein interaction network via STRING and pinpointing 11 hub targets such as EGFR, AKT1, ERBB2, MET, IGF1, CASP3, HSP90AA1, HIF1A, MMP2, HGF, and MMP9 with CytoHuba. Utilizing DAVID, Gene Ontology (GO) analysis highlighted metastasis-related processes such as epithelial–mesenchymal transition, positive regulation of cell migration, and key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, including cancer, prostate cancer, PI3K-Akt, and MAPK signaling, while the web resources such as UALCAN and GEPIA2 affirmed the clinical significance of the top 11 hub targets in mPC patient survival analysis and gene expression patterns. Our innovative GMFA enrichment method further enriched network pharmacology findings. Molecular docking analyses demonstrated substantial interactions between MAT and 11 hub targets. Simulation studies confirmed the stable interactions of MAT with selected targets. Experimental validation in PC3 cells, employing quantitative real-time reverse-transcription PCR and various cell-based assays, corroborated MAT’s antimetastatic effects on mPC. Thus, this exhaustive NP analysis, complemented by GMFA, molecular docking, molecular dynamics simulations, and experimental validations, underscores MAT’s multifaceted role in targeting mPC through diverse therapeutic avenues. Nevertheless, comprehensive in vitro validation is imperative to solidify these findings.
期刊介绍:
Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data.
The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.