School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
School of Integrated Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
J Ethnopharmacol. 2022 Dec 5;299:115546. doi: 10.1016/j.jep.2022.115546. Epub 2022 Jul 15.
Salvia miltiorrhiza Bunge and Panax ginseng C. A. Meyer have special curative effect on cancer treatment. The optimizing component formula (OCF) extracted from those two herbs was in line with the anti-lung cancer treatment principle of activating blood and supplementing 'Qi'. However, the study on the mechanism of component formula has always been an insurmountable challenge. Nowadays, the application of network pharmacology and artificial intelligence (AI) in the field of TCM provides new ideas for the study of new targets and mechanisms of TCM, which promotes the modernization of TCM.
This study aims to further explore the anti-lung cancer mechanism of OCF by using an integrated strategy of network pharmacology and AI technology.
Bioinformatic analysis was used to analyze the expression levels, prognosis and survival of DTL and PDCD4 in cancer patients. The binding strength of OCF and DTL was simulated by molecular docking, and the affinity between them was detected by Bio-layer interferometry. Network pharmacology was used to predict the active components, potential targets and pathways of OCF. The association between key targets and their corresponding components and DTL was analyzed by Ingenuity Pathway Analysis (IPA). MTT assay, colony formation assay, wound-healing assay and transwell assay were used to verify the inhibitory effects of OCF on lung cancer cells in vitro. qRT-PCR and Western blot assay were used to detect the effects of OCF on mRNA and protein expression of DTL, PDCD4 and key genes in MAPK/JNK pathways.
Bioinformatics analysis showed that DTL was significantly up-regulated in lung cancer, which was associated with high malignancy rate, high metastasis rate and poor prognosis of primary tumor. PDCD4 was down-regulated in lung cancer, and associated with high metastasis rate and poor prognosis. The good affinity between OCF and DTL was predicted and verified by molecular docking and Bio-layer interferometry. Based on the network pharmacological databases, 40 active components and 220 corresponding targets of OCF were screened out. KEGG analysis showed that OCF component targets were mainly enriched in MAPK signaling pathway. IPA results showed the interrelationship between DTL, PDCD4, MAPK pathway genes and their corresponding OCF components. In addition, in vitro experiments demonstrated anti-lung cancer activity of OCF, as validated, via impairing cell viability and cell proliferation, as well as inhibiting migration and invasion abilities in lung cancer cells. qRT-PCR showed that OCF down-regulated the mRNA expression of DTL, MAP4K1, JNK, c-Jun and c-Myc, and up-regulated the mRNA expression of PDCD4 and P53 genes in A549 lung cancer cells. Western blot suggested that OCF suppressed the protein level of DTL and blocked the ubiquitination of PDCD4 in A549 lung cancer cells, and down-regulated the protein levels of MAP4K1, p-JNK and p-c-Jun while up-regulated the proteins expression level of P53.
OCF might elicit an anti-lung cancer effect by blocking DTL-mediated PDCD4 ubiquitination and suppression of the MAPK/JNK pathway. Meanwhile, our work revealed that network pharmacology and AI technology strategy are cogent means of studying the active components and mechanism of TCM.
草药丹参和人参对癌症治疗有特殊疗效。从这两种草药中提取的优化成分配方（OCF）符合激活血液和补充“气”的肺癌治疗原则。然而，成分配方机制的研究一直是一个不可逾越的挑战。如今，网络药理学和人工智能（AI）在中医药领域的应用为中医药新靶点和新机制的研究提供了新思路，推动了中医药的现代化。
本研究旨在采用网络药理学和人工智能技术的综合策略，进一步探讨 OCF 的抗癌机制。
通过生物信息学分析，分析癌症患者 DTL 和 PDCD4 的表达水平、预后和生存情况。通过分子对接模拟 OCF 与 DTL 的结合强度，并通过生物层干涉法检测它们之间的亲和力。网络药理学预测 OCF 的活性成分、潜在靶点和途径。通过 Ingenuity Pathway Analysis（IPA）分析关键靶标与其对应成分和 DTL 的相关性。MTT 检测、集落形成检测、划痕愈合检测和 Transwell 检测用于体外验证 OCF 对肺癌细胞的抑制作用。qRT-PCR 和 Western blot 检测 OCF 对 DTL、PDCD4 和 MAPK/JNK 通路关键基因 mRNA 和蛋白表达的影响。
生物信息学分析表明，DTL 在肺癌中显著上调，与原发性肿瘤的高恶性率、高转移率和不良预后有关。PDCD4 在肺癌中下调，与高转移率和不良预后有关。分子对接和生物层干涉验证了 OCF 与 DTL 之间的良好亲和力。基于网络药理学数据库，筛选出 OCF 的 40 种活性成分和 220 种相应靶点。KEGG 分析表明，OCF 成分靶标主要富集在 MAPK 信号通路中。IPA 结果显示了 DTL、PDCD4、MAPK 通路基因及其相应 OCF 成分之间的相互关系。此外，体外实验证明了 OCF 在肺癌细胞中具有抗癌活性，通过损伤细胞活力和增殖，以及抑制迁移和侵袭能力得到验证。qRT-PCR 显示，OCF 下调 A549 肺癌细胞中 DTL、MAP4K1、JNK、c-Jun 和 c-Myc 的 mRNA 表达，上调 PDCD4 和 P53 基因的 mRNA 表达。Western blot 表明，OCF 抑制 A549 肺癌细胞中 DTL 的蛋白水平，并阻断 PDCD4 的泛素化，同时下调 MAP4K1、p-JNK 和 p-c-Jun 的蛋白水平，上调 P53 的蛋白表达水平。
OCF 可能通过阻断 DTL 介导的 PDCD4 泛素化和抑制 MAPK/JNK 通路来发挥抗癌作用。同时，我们的工作表明，网络药理学和人工智能技术策略是研究中药活性成分和机制的有效手段。
