Evidence map›Paper›PMID 40478357›Full record

ArticleDiscover oncology2025

Unveiling the mechanisms of Tianjihuang in hepatocellular carcinoma: a network pharmacology and molecular docking study.

Bixing Liang, Wenyu Wu, Fan He, Bing Yang, Dongxin Tang

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Bixing LiangGuizhou University of Traditional Chinese Medicine, Guiyang, 550005, China.
Wenyu WuThe First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine oncology department, No.50 Shidong Road, Nanming District, Guiyang, 550001, Guizhou, China.
Fan HeThe First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine oncology department, No.50 Shidong Road, Nanming District, Guiyang, 550001, Guizhou, China.
Bing YangThe First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine oncology department, No.50 Shidong Road, Nanming District, Guiyang, 550001, Guizhou, China.
Dongxin TangThe First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine oncology department, No.50 Shidong Road, Nanming District, Guiyang, 550001, Guizhou, China. tangdongxin@sina.com.

Funding

Medical Translation Engineering Research Center of Chinese Medicine and Ethnic Medicine for Preventing and Treating Tumors in Guizhou Higher Education Institutions Guizhou Education and Technology [2023] No. 037Talent Base for TCM Tumor Inheritance and Scientific and Technological Innovation in Guizhou Province Guizhou Human Leadership Development [2018] No. 3
6 · The paper itself

Abstract

backgroundHepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, with limited therapeutic options and poor long-term survival. Hypericum japonicum Thunb. (Tianjihuang), a traditional Chinese medicine exhibits promising anticancer properties. This study aims to elucidate the multi-target mechanisms of Tianjihuang in treating HCC using network pharmacology and molecular docking techniques.

methodsThe active components of Tianjihuang and their targets were retrieved from TCMSP, PubChem, and Swiss Target Prediction databases. HCC-related targets were identified using GeneCard, OMIM, and TTD databases, and overlapping targets were analyzed. Protein-protein interaction (PPI) networks were constructed and analyzed using Cytoscape. Functional enrichment analysis of key targets was performed via GO and KEGG pathways. Kaplan-Meier curves assessed the clinical relevance of core targets, and molecular docking evaluated the binding affinities between Tianjihuang components and key targets.

resultsTianjihuang contained seven bioactive components targeting 207 genes, with 77 overlapping HCC-related targets. PPI analysis identified key targets, including AKT1, STAT3, EGFR, and ESR1, which play pivotal roles in HCC pathogenesis. GO and KEGG analysis revealed that Tianjihuang's anti-HCC effects involve multiple biological processes and pathways, such as cell proliferation, apoptosis, and PI3K-Akt signaling. Molecular docking results showed high binding affinities of key components, such as quercetin and gallic acid, with core targets supporting their potential therapeutic effects.

conclusionThis study demonstrates that Tianjihuang exerts its anti-HCC effects through a multi-component, multi-target, and multi-pathway mechanism. These findings provide a scientific foundation for the clinical application of Tianjihuang and highlight its potential as a complementary therapy for HCC.

Indexed as

Hepatocellular carcinomaMolecular dockingMulti-target therapyNetwork pharmacologyTianjihuang

Identifiers

PMID40478357
PMCPMC12144007

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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.