Determining potential therapeutic targets for venous thrombosis through network pharmacology, cluster typing, WGCNA, machine learning, immune infiltration analysis, and ceRNA networks

Venous thrombosis presents a significant global health challenge, characterized by its high incidence and limited therapeutic effectiveness. Our objective is to leverage the pharmacological insights offered by traditional Chinese medicine networks to identify potential therapeutic targets for venous thrombosis treatment and elucidate their underlying mechanisms of action. We initiated our study by isolating the active ingredients and targets of Chinese medicine compounds from the traditional Chinese medicine systems pharmacology database. Concurrently, we acquired venous thromboembolism (VTE) patient data from the gene expression omnibus dataset. Utilizing cytoscape, we constructed a network connecting traditional Chinese medicine ingredients, disease targets, and related interactions. Molecular subtypes were determined through target information clustering and typing using the "ConsensusClusterPlus" software package. Key genes were subsequently identified through a combination of weighted gene co-expression network analysis and machine learning techniques. Functional enrichment analysis was performed on these key genes. Subsequently, we investigated immune cell and immune function differences related to the identified key genes. Lastly, we constructed the competing endogenous RNA network associated with PPP2R1A. Our initial analysis identified several key genes, including FOS, ICAM1, CASP3, and HSP90AA1. Subsequent functional and downstream analyses revealed that 2 central hub genes, PPP2R1A and ribosomal protein L9, may represent novel targets for VTE therapy. Notably, these hub genes are not only associated with thrombospondin and platelet function regulation but also play a role in modulating T cell expression in immunoassays. In conclusion, our findings suggest that 10 long non-coding RNAs may compete with 2 microRNAs for binding, thereby regulating PPP2R1A target genes, with potential implications for improving VTE treatment efficacy. Our current findings offer a novel direction and serve as a theoretical foundation for identifying therapeutic targets in the treatment of VTE. Furthermore, these findings hold the potential to facilitate the translation of our research into clinical applications in the future.

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Journal
Medicine
Published
2025-11-28
DOI
https://doi.org/10.1097/md.0000000000043018
Primary Topic
Traditional Chinese Medicine Analysis
Type
article
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article

Determining potential therapeutic targets for venous thrombosis through network pharmacology, cluster typing, WGCNA, machine learning, immune infiltration analysis, and ceRNA networks

Xishi Sun, Zhuoji Li, Junfen Cheng, Jie Sun et al.
Medicine
Traditional Chinese Medicine Analysis
article

Determining potential therapeutic targets for venous thrombosis through network pharmacology, cluster typing, WGCNA, machine learning, immune infiltration analysis, and ceRNA networks

Xishi Sun, Zhuoji Li, Junfen Cheng, Jie Sun, Kaili Fu, Lingpin Pang, Tao Huang, Dingyu Guo, Lingyue Song, Ming Zhong
article en

Abstract

Venous thrombosis presents a significant global health challenge, characterized by its high incidence and limited therapeutic effectiveness. Our objective is to leverage the pharmacological insights offered by traditional Chinese medicine networks to identify potential therapeutic targets for venous thrombosis treatment and elucidate their underlying mechanisms of action. We initiated our study by isolating the active ingredients and targets of Chinese medicine compounds from the traditional Chinese medicine systems pharmacology database. Concurrently, we acquired venous thromboembolism (VTE) patient data from the gene expression omnibus dataset. Utilizing cytoscape, we constructed a network connecting traditional Chinese medicine ingredients, disease targets, and related interactions. Molecular subtypes were determined through target information clustering and typing using the "ConsensusClusterPlus" software package. Key genes were subsequently identified through a combination of weighted gene co-expression network analysis and machine learning techniques. Functional enrichment analysis was performed on these key genes. Subsequently, we investigated immune cell and immune function differences related to the identified key genes. Lastly, we constructed the competing endogenous RNA network associated with PPP2R1A. Our initial analysis identified several key genes, including FOS, ICAM1, CASP3, and HSP90AA1. Subsequent functional and downstream analyses revealed that 2 central hub genes, PPP2R1A and ribosomal protein L9, may represent novel targets for VTE therapy. Notably, these hub genes are not only associated with thrombospondin and platelet function regulation but also play a role in modulating T cell expression in immunoassays. In conclusion, our findings suggest that 10 long non-coding RNAs may compete with 2 microRNAs for binding, thereby regulating PPP2R1A target genes, with potential implications for improving VTE treatment efficacy. Our current findings offer a novel direction and serve as a theoretical foundation for identifying therapeutic targets in the treatment of VTE. Furthermore, these findings hold the potential to facilitate the translation of our research into clinical applications in the future.

MedicineVol. 104(48)
Guangdong Medical College (CN), Second Affiliated Hospital of Guangzhou Medical University (CN), Guangzhou Medical University (CN)
Openalex Percentile: Top 45%
Traditional Chinese Medicine Analysis
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