This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Guanglong Huang
Southern Medical University Nanfang Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-1589-9202
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Xuefu Zhuyu Decoction (XFZYD) is a well-known Traditional Chinese Medicine (TCM) formula that has many pharmacological effects, including enhancing immune function, improving hemorheology and regulating blood vessels bidirectionally. Modern pharmacological and clinical studies showed that XFZYD could ameliorate curative effect of glioblastoma (GBM). The aim of this study was to interpret core components and the hidden molecular mechanisms of XFZYD on GBM.
Methods
Here, a novel network pharmacology strategy, which combined pharmacological data, next generation sequencing data, pharmacokinetic parameters and a novel node importance calculation method was designed to decipher the potential therapeutic mechanism of XFZYD on GBM. The partial components in core component group (CCG) were evaluated by in vitro expriments. We identified 117 chemical components analysis through ADME screening, then component-target network and GBM related genes were integrated as the component-target-pathogenic gene (C-T-P) network.
Results
The results show that the enriched pathways of targets in the key functional network could cover 77.92% of the enriched pathways of pathogenic genes. A novel cumulative contribution rate (CCR) calculation model was designed and captured CCG with 21 components. The statistics results indicate that 15 enriched pathways of the targets of CCG were overlap with pathogenic genes enriched pathways. Finally, some core components in CCG were validated by in vitro experiments.
Conclusion
The results show that our proposed stategy for decoding CCG and infering the underlying mechanism with good reliability and accuracy. The validation results indicate that the CCG play a therapeutic role on GBM by targeting to PI3K-Akt signaling pathway and Toll-like receptor signaling pathway. Our strategy provides methodological reference for the optimization and secondary development of TCM formula.
Keywords
Xuefu Zhuyu Decoction, glioblastoma, network pharmacology, key functional network, cumulative contribution rate
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This is a list of supplementary files associated with this preprint. Click to download.
- SupplementaryfigureS1.tif
The heatmap of the differential expression genes in GBM.
- SupplementaryfigureS2.tif
The comprehensive PPI network.
- SupplementaryfigureS3.tif
Pathway enrichment analysis (A) and GO anlysis (B) of GBM-weighted genes.
- SupplementaryfigureS4.tif
Weighted gene network of GBM. The size of the node represents the square root of the two |log 2(fold change)|, and the nodes with the gradient from green to red represent the down-regulated gene gradient to the up-regulated gene of GBM.
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Research
Guanglong Huang
Southern Medical University Nanfang Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-1589-9202
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 11 Jan, 2021
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Neurosurgery
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background
Xuefu Zhuyu Decoction (XFZYD) is a well-known Traditional Chinese Medicine (TCM) formula that has many pharmacological effects, including enhancing immune function, improving hemorheology and regulating blood vessels bidirectionally. Modern pharmacological and clinical studies showed that XFZYD could ameliorate curative effect of glioblastoma (GBM). The aim of this study was to interpret core components and the hidden molecular mechanisms of XFZYD on GBM.
Methods
Here, a novel network pharmacology strategy, which combined pharmacological data, next generation sequencing data, pharmacokinetic parameters and a novel node importance calculation method was designed to decipher the potential therapeutic mechanism of XFZYD on GBM. The partial components in core component group (CCG) were evaluated by in vitro expriments. We identified 117 chemical components analysis through ADME screening, then component-target network and GBM related genes were integrated as the component-target-pathogenic gene (C-T-P) network.
Results
The results show that the enriched pathways of targets in the key functional network could cover 77.92% of the enriched pathways of pathogenic genes. A novel cumulative contribution rate (CCR) calculation model was designed and captured CCG with 21 components. The statistics results indicate that 15 enriched pathways of the targets of CCG were overlap with pathogenic genes enriched pathways. Finally, some core components in CCG were validated by in vitro experiments.
Conclusion
The results show that our proposed stategy for decoding CCG and infering the underlying mechanism with good reliability and accuracy. The validation results indicate that the CCG play a therapeutic role on GBM by targeting to PI3K-Akt signaling pathway and Toll-like receptor signaling pathway. Our strategy provides methodological reference for the optimization and secondary development of TCM formula.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
This is a list of supplementary files associated with this preprint. Click to download.
- SupplementaryfigureS1.tif
The heatmap of the differential expression genes in GBM.
- SupplementaryfigureS2.tif
The comprehensive PPI network.
- SupplementaryfigureS3.tif
Pathway enrichment analysis (A) and GO anlysis (B) of GBM-weighted genes.
- SupplementaryfigureS4.tif
Weighted gene network of GBM. The size of the node represents the square root of the two |log 2(fold change)|, and the nodes with the gradient from green to red represent the down-regulated gene gradient to the up-regulated gene of GBM.
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