ArticleMedical science monitor : international medical journal of experimental and clinical research2019
The Effects of Plumbagin on Pancreatic Cancer: A Mechanistic Network Pharmacology Approach.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 42 citations in OpenAlex.
- Astaxanthin alleviates autophagy, inflammation, and oxidative stress in ventilator-associated lung injury rats by inhibiting MAPK/ERK1/2 pathway.Acta cirurgica brasileira · 2026Article
- Natural Compounds as Potential Therapeutics for Pancreatic Cancer: A Narrative Review.Current drug metabolism · 2025Review
- The phytochemical plumbagin: mechanism behind its "pleiotropic" nature and potential as an anticancer treatment.Archives of toxicology · 2024Review
- Astaxanthin Alleviates Chronic Prostatitis via the ERK1/2 Signaling Pathway: Evidence from Network Pharmacology and Experimental Validation.Combinatorial chemistry & high throughput screening · 2024Article
- Pharmacological Features and Therapeutic Implications of Plumbagin in Cancer and Metabolic Disorders: A Narrative Review.Nutrients · 2024Review
- Prognostic implication of downregulated exosomal miRNAs in patients with sepsis: a cross-sectional study with bioinformatics analysis.Journal of intensive care · 2023Article
- Anti-ovarian cancer actions and pharmacological targets of plumbagin.Naunyn-Schmiedeberg's archives of pharmacology · 2023Article
- Identification of autophagy-related genes in neuropathic pain through bioinformatic analysis.Hereditas · 2023Article
- Synthesis and Characterization of Plumbagin S-Allyl Cysteine Ester: Determination of Anticancer Activity In Silico and In Vitro.Applied biochemistry and biotechnology · 2022Article
- Article
- Exploring anti-liver cancer targets and mechanisms of oxyresveratrol:Bioengineered · 2021Article
- Systematic analysis of the lysine malonylome in Sanghuangporus sanghuang.BMC genomics · 2021Article
- Integrated Microarray to Identify the Hub miRNAs and Constructed miRNA-mRNA Network in Neuroblastoma Via Bioinformatics Analysis.Neurochemical research · 2021Article
- A Network Pharmacology Approach to Investigate the Mechanism of Erjing Prescription in Type 2 Diabetes.Evidence-based complementary and alternative medicine : eCAM · 2021Article
- Medical Significance of Uterine Corpus Endometrial Carcinoma Patients Infected With SARS-CoV-2 and Pharmacological Characteristics of Plumbagin.Frontiers in endocrinology · 2021Article
- Molecular docking analysis of flupenthixol and desmethylastemizole with the apoptotic regulator proteins CFLAR and TRAF2 linked to lung carcinoma.Bioinformation · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND This study aimed to use a network pharmacology approach to establish the effects of plumbagin on pancreatic cancer (PC) and to predict core targets and biological functions, pathways, and mechanisms of action. MATERIAL AND METHODS Genes associated with the pathogenesis of PC were obtained from a database of gene-disease associations (DisGeNET). Putative genes associated with plumbagin were identified from the databases of drug target identification (PharmMapper), target prediction of bioactive components (SwissTargetPrediction), and comprehensive drug target information (DrugBank). PC targets of plumbagin were harvested by using a functional enrichment analysis tool (FunRich). The data of function-related protein-protein interactions (PPIs) with a confidence score >0.9 were obtained by using functional protein association networks (STRING). The network interactions of plumbagin and PC targets and function-related proteins were constructed through complex network analysis and visualization (Cytoscape). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were used to identify the effects of plumbagin. RESULTS The most important biotargets for plumbagin in PC were identified as TP53, MAPK1, BCL2, and IL6. A total of 1,731 annotations and 121 enriched pathways for plumbagin and PC were identified by KEGG and GO analysis. The top 10 signaling pathways of plumbagin and PC were screened, followed by identification of biological components and functions. CONCLUSIONS Network pharmacology established the effects of plumbagin on PC, predicted core targets, biological functions, pathways, and mechanisms of action. Further studies are needed to validate these predictive biotargets in PC.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.