Integrating network pharmacology prediction and experimental investigation to verify ginkgetin anti-invasion and metastasis of human lung adenocarcinoma cells via the Akt/GSK-3β/Snail and Wnt/β-catenin pathway
Lung cancer, one of the most frequent malignancies, has a high death rate and an increased number of new cases globally. Ginkgo biloba has been used for many years in the treatment of lung cancer. Ginkgetin is the key active ingredient extracted from Ginkgo biloba. However, the mechanism by which gi...
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Veröffentlicht in: | Frontiers in pharmacology 2023-03, Vol.14, p.1135601-1135601 |
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Sprache: | eng |
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Zusammenfassung: | Lung cancer, one of the most frequent malignancies, has a high death rate and an increased number of new cases globally. Ginkgo biloba has been used for many years in the treatment of lung cancer. Ginkgetin is the key active ingredient extracted from Ginkgo biloba. However, the mechanism by which ginkgetin inhibits the invasive metastasis of lung cancer is unclear.
We used a network pharmacology approach to obtain the molecular mechanism by which ginkgetin inhibits lung cancer metastasis. Then we analyzed potential target proteins between ginkgetin and lung cancer. Finally, we validated with molecular docking and experimental validation.
By analyzing the intersecting genes of lung cancer and ginkgetin, there were 79 intersecting genes, which were mainly involved in the positive regulation of cell migration, with the cancer pathway being one of the most enriched pathways. The results of
experiments showed that GK had a large inhibitory effect on cell invasion and metastasis of A549 and H1299.
animals GK had a great inhibitory effect on metastasis of LLC.
This study identified the potential related GK molecular targets and signaling pathways in treating human lung cancer using network pharmacological approaches. Experiments confirmed that GK inhibits the Akt/GSK-3β/Snail and Wnt/β-catenin cascade initiation in A549, H1299 and LLC cells, preventing metastasis. This study's results align with the hypotheses derived from the network pharmacology analysis. |
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ISSN: | 1663-9812 1663-9812 |
DOI: | 10.3389/fphar.2023.1135601 |