Novel systems biology experimental pipeline reveals matairesinol's antimetastatic potential in prostate cancer: an integrated approach of network pharmacology, bioinformatics, and experimental validation.

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.

Decoding the therapeutic landscape of alpha-linolenic acid: a network pharmacology and bioinformatics investigation against cancer-related epigenetic modifiers.

Omega-3 (n - 3) and omega-6 (n - 6) polyunsaturated fatty acids (PUFAs) are vital for human health, but an imbalance between these types is associated with chronic diseases, including cancer. Alpha-linolenic acid (ALA), a n - 3 PUFA, shows promise as an anticancer agent in both laboratory and animal studies. However, the precise molecular mechanisms underlying ALA's actions against cancer-related epigenetic modifiers (CaEpM) remain unclear. To understand this, we employed network pharmacology (NP) and molecular docking techniques. Our study identified 51 potential ALA targets and GO and KEGG pathway analysis revealed possible molecular targets and signaling pathways of ALA against CaEpM. From PPI analysis, EZH2, KAT2B, SIRT1, KAT2A, KDM6B, EHMT2, WDR5, SETD7, SIRT2, and HDAC3 emerged as the top 10 potential targets. Additionally, GeneMANIA functional association (GMFA) network analysis of these top 10 targets was performed to enhance NP insights and explore ALA's multi-target approach. After an exhaustive analysis of the core FGN subnetwork, it became evident that 9 out of the 15 targets-namely EZH2, SUZ12, EED, PARP1, HDAC3, DNMT1, NCOR2, KAT2B, and TRRAP-manifested evidently strong and abundant interconnections among each other. Molecular docking of both top 10 targets and core FGN targets confirmed strong binding affinity between ALA and SIRT2, WDR5, KDM6B, EHMT2, HDAC3, EZH2, PARP1, and KAT2B, underscoring their roles in ALA's anti-CaEpM mechanism. Our findings suggest that ALA may target key signaling pathways related to transcriptional regulation, microRNA involvement, stem cell pluripotency and cellular senescence in cancer epigenetics. These findings illuminate ALA's potential as a multi-target agent against CaEpM.Communicated by Ramaswamy H. Sarma.