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Anticancer drug discovery from Iranian Chrysanthemum cultivars through system pharmacology exploration and experimental validation.

ABSTRACT: Breast cancer is the most common carcinoma in women, and natural products would be effective preventing some side effects of cancer treatment. In the present study, cytotoxic activities of different Iranian Chrysanthemum morifolium cultivars were evaluated in human breast cancer cell lines (MCF-7) and human lymphocytes. A systems pharmacology approach was employed between major compounds of these cultivars (chlorogenic acid, luteolin, quercetin, rutin, ferulic acid, and apigenin) and known breast cancer drugs (tucatinib, methotrexate, tamoxifen, and mitomycin) with 22 breast cancer-related targets to analyze the mechanism through which Chrysanthemum cultivars act on breast cancer. Target validation was performed by the molecular docking method. The results indicated that Chrysanthemum extracts inhibited the proliferation of MCF7 cells in a dose- and cultivar-dependent manner. In all studied cultivars, the most effective extract concentration with the lowest viability of MCF-7 cells, was as much as 312 µg ml^-1. Also, higher concentrations of the extracts (> 1000 µg ml^-1) reduced the lymphocyte cell viability, demonstrating that these doses were toxic. The gene ontology analysis revealed the therapeutic effects of Chrysanthemum's active compounds on breast cancer by regulating the biological processes of their protein targets. Moreover, it has been documented that rutin, owing to its anticancer effects and several other health benefits, is a promising multi-targeted herbal ingredient. Finally, the present study compared different Iranian Chrysanthemum cultivars to provide new insights into useful pharmaceutical applications.

SUBMITTER: Hodaei M

PROVIDER: S-EPMC8175602 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The quintessential biological response to disease is inflammation. It is a driver and an important element in a wide range of pathological states. Pharmacological management of inflammation is therefore central in the clinical setting. Anti-inflammatory drugs modulate specific molecules involved in the inflammatory response; these drugs are traditionally classified as steroidal and non-steroidal drugs. However, the effects of these drugs are rarely limited to their canonical targets, affecting other molecules and altering biological functions with system-wide effects that can lead to the emergence of secondary therapeutic applications or adverse drug reactions (ADRs). In this study, relationships among anti-inflammatory drugs, functional pathways, and ADRs were explored through network models. We integrated structural drug information, experimental anti-inflammatory drug perturbation gene expression profiles obtained from the Connectivity Map and Library of Integrated Network-Based Cellular Signatures, functional pathways in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Reactome databases, as well as adverse reaction information from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The network models comprise nodes representing anti-inflammatory drugs, functional pathways, and adverse effects. We identified structural and gene perturbation similarities linking anti-inflammatory drugs. Functional pathways were connected to drugs by implementing Gene Set Enrichment Analysis (GSEA). Drugs and adverse effects were connected based on the proportional reporting ratio (PRR) of an adverse effect in response to a given drug. Through these network models, relationships among anti-inflammatory drugs, their functional effects at the pathway level, and their adverse effects were explored. These networks comprise 70 different anti-inflammatory drugs, 462 functional pathways, and 1,175 ADRs. Network-based properties, such as degree, clustering coefficient, and node strength, were used to identify new therapeutic applications within and beyond the anti-inflammatory context, as well as ADR risk for these drugs, helping to select better repurposing candidates. Based on these parameters, we identified naproxen, meloxicam, etodolac, tenoxicam, flufenamic acid, fenoprofen, and nabumetone as candidates for drug repurposing with lower ADR risk. This network-based analysis pipeline provides a novel way to explore the effects of drugs in a therapeutic space.

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Anticancer drug discovery from Iranian Chrysanthemum cultivars through system pharmacology exploration and experimental validation.

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