4.7 Article

Integrated omics profiling and network pharmacology uncovers the prognostic genes and multi-targeted therapeutic bioactives to combat lung cancer

期刊

EUROPEAN JOURNAL OF PHARMACOLOGY
卷 940, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.ejphar.2022.175479

关键词

Cheminformatics; Integrative omics; Lung cancer; Molecular docking; Phytocompounds; Network pharmacology

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This pilot study used various methods including network pharmacology, cheminformatics, integrative omics, molecular docking, and in vitro anti-cancer analysis to uncover the multi-targeted treatment mechanisms of novel plant bioactives in treating lung cancer. The study found that bioactive molecules from medicinal plants can efficiently target 390 human and lung cancer associated genes, and identified 7 bioactive molecules significantly targeting 8 lung cancer genes. In addition, unique genes between lung cancer and normal lung tissues were discovered and validated, and lupeol and p-coumaric acid exhibited high binding affinities with MIF, CCNB1, and FABP4.
Non-small cell lung cancer (NSCLC) is the frequent subtype of lung cancer and the currently used treatment methods, diagnosis, and chemoresistance are relatively ineffective. Determining the pharmacological targets from active biomolecules of medicinal plants has become a frontiers era for biomedical research to develop novel therapies. In view of these scenarios, this pilot study, network pharmacology, cheminformatics, integrative omics, molecular docking and in vitro anti-cancer analysis were performed to unveil the multi-targeted treatment mechanisms of novel plant bioactives to treat lung cancer. Bioactive molecules from medicinal plants were compiled from PubChem. Network pharmacology approach revealed that 29 compounds efficiently target the 390 human and lung cancer associated genes. In addition, comparative analysis was performed and identified the 7 bioactive molecules significantly targeting 8 lung cancer genes. The integrative omics analysis discovered unique genes between the lung cancer and normal lung tissues. These genes were further validated through protein-protein interaction, gene ontology, gene functional and pathway enrichment, boxplot and overall sur-vival analyses to understand the function of unique genes and their involvement in cancer signaling pathways. Survival heatmap analyses identified the significant prognostic genes. Docking results revealed that, lupeol and p-coumaric acid displayed high binding affinities with MIF, CCNB1, FABP4. Hence, we selected these two bio-actives for in vitro analysis. Furthermore, these selected bioactives were showed concentration dependent cytotoxicity against the lung adenocarcinoma cells (A549). This holistic study has opened up novel avenues and unravels the cancer prognostic genes which could serve as druggable target and bioactives with anti-cancerous efficacy. Further functional validations are prerequisites to deciphering these bioactives as commercial drug candidates.

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