ArticleBMC complementary medicine and therapies2020
A bioinformatics investigation into the pharmacological mechanisms of javanica oil emulsion injection in non-small cell lung cancer based on network pharmacology methodologies.
Article in BMC complementary medicine and therapies, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Decoding the therapeutic promise of Solanum trilobatum in oral submucous fibrosis: a network pharmacology, docking, and bioactivity study.Scientific reports · 2026Article
- Development and validation of a delirium prediction model for hospitalized older medical patients: a prospective cohort study.BMC geriatrics · 2025Article
- Identification of Novel Marine Bioactive Compound as Potential Multiple Inhibitors in Triple-negative Breast Cancer - AnCurrent computer-aided drug design · 2025Article
- Oleic Acid Inhibits SDC4 and Promotes Ferroptosis in Lung Cancer Through GPX4/ACSL4.The clinical respiratory journal · 2024Article
- Development and internal and external validation of a nomogram model for frailty risk among hospitalised older people using comprehensive geriatric assessment data.BMC geriatrics · 2023Article
- Article
- Exploring the Multicomponent Synergy Mechanism of Yinzhihuang Granule in Inhibiting Inflammation-Cancer Transformation of Hepar Based on Integrated Bioinformatics and Network Pharmacology.BioMed research international · 2022Article
- Effect of alkylglycerone phosphate synthase on the expression levels of lncRNAs in glioma cells and its functional prediction.Oncology letters · 2020Article
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
Abstract
backgroundJavanica oil emulsion injection (JOEI) is an effective therapeutic option for patients with non-small cell lung cancer (NSCLC), but its mechanisms have not been fully elucidated.
methodsIn this study, we utilized network pharmacology to systematically investigate the bioactive components and targets of JOEI, identify common targets in NSCLC, and understand and evaluate the underlying mechanism of JOEI in the treatment of NSCLC through expression level, correlation, enrichment, Cox, survival and molecular docking analyses. The results indicated that five compounds of JOEI interact with five pivotal targets (LDLR, FABP4, ABCB1, PTGS2, and SDC4) that might be strongly correlated with the JOEI-mediated treatment of NSCLC.
resultsThe expression level analysis demonstrated that NSCLC tissues exhibit low expression of FABP4, ABCB1, LDLR and PTGS2 and high SDC4 expression. According to the correlation analysis, a decrease in FABP4 expression was strongly correlated with decreases in LDLR and ABCB1, and a decrease in LDLR was strongly correlated with decreased PTGS2 and increased in SDC4 expression. Cox and survival analyses showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group (p = 0.00388). In the survival analysis, the area under the curve (AUC) showed that the pivotal gene model exhibited the best predictive capacity over 4 years (AUC = 0.613). Moreover, the molecular docking analysis indicated that LDLR, FABP4, ABCB1, PTGS2 and SDC4 exhibit good binding activity with the corresponding compounds.
conclusionIn conclusion, this study predicted and verified that the mechanism of JOEI against NSCLC involves multiple targets and signaling pathways. Furthermore, this study provides candidate targets for the treatment of NSCLC, lays a good foundation for further experimental research and promotes the reasonable application of JOEI in clinical treatment.
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