Fusion of core pathways reveals a horizontal synergistic mechanism underlying combination therapy

Wang, Zhong; Jing, Zhiwei; Zhou, Cai-Xiu; Zhang, Liang; Cheng, Jing; Zhang, Zhanjun; Li, Jun; Xu, Chi; Li, Peng-Tao; Wang, Yongyan

doi:10.1016/j.ejphar.2011.05.046

Cited by 23 publications

(46 citation statements)

References 44 publications

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“…The cDNA microarray, including 374 cDNA ischemia-related genes, was selected from the Science STKE database. The details of this process are described in our previous studies [21][22][23][24][25][26] .…”

Section: Rna Extraction and Microarraymentioning

confidence: 99%

“…The level of statistical significance was set at P<0.05. Finally, canonical pathways with a P value<0.05 and a >1.5-fold change were screened out and analyzed [21][22][23][24][25][26] .…”

Section: Rna Extraction and Microarraymentioning

confidence: 99%

“…Images of these slices were captured by a digital camera (Color CCD camera TP-6001A, Topica Inc, Tokyo, Japan). The area of the infarction region was calculated using a Pathology Image Analysis System (Topica Inc), and the ratio of the infarction volume to the total slice volume was calculated as described in our previous study [21][22][23][24][25][26] .…”

Section: Drug Administrationmentioning

confidence: 99%

“…The results were submitted to the Array Express database. All data were normalized by locally weighted scatter plot smoothing (Lowness) to reduce experimental variability [21][22][23][24][25][26] . One-way analysis of variance and significant analysis of micro-arrays were employed to compare the mean numbers of the altered genes between the vehicle and sham, CM and vehicle, UA and CM, JA and CM, and JU and CM groups.…”

Section: Rna Extraction and Microarraymentioning

confidence: 99%

“…Our previous studies have shown that ursodeoxycholic acid (UA) and jasminoidin (JA) can significantly reduce ischemic infarct volume [21][22][23][24][25] . In the current study, we further explored the pure synergistic mechanism of these drugs, excluding interference from any negative phenotype compounds.…”

Section: Introductionmentioning

confidence: 99%

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Phenotype-dependent alteration of pathways and networks reveals a pure synergistic mechanism for compounds treating mouse cerebral ischemia

Wang

et al. 2015

Acta Pharmacol Sin

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Aim: Our previous studies have showed that ursodeoxycholic acid (UA) and jasminoidin (JA) effectively reduce cerebral infarct volume in mice. In this study we explored the pure synergistic mechanism of these compounds in treatment of mouse cerebral ischemia, which was defined as synergistic actions specific for phenotype variations after excluding interference from ineffective compounds. Methods: Mice with focal cerebral ischemia were treated with UA, JA or a combination JA and UA (JU). Concha margaritifera (CM) was taken as ineffective compound. Cerebral infarct volume of the mice was determined, and the hippocampi were taken for microarray analysis. Particular signaling pathways and biological functions were enriched based on differentially expressed genes, and corresponding networks were constructed through Ingenuity Pathway Analysis. Results: In phenotype analysis, UA, JA, and JU significantly reduced the ischemic infarct volume with JU being superior to UA or JA alone, while CM was ineffective. As a result, 4 pathways enriched in CM were excluded. Core pathways in the phenotype-positive groups (UA or JA) were involved in neuronal homeostasis and neuropathology. JU-contributing pathways included all UA-contributing and the majority (71.7%) of JA-contributing pathways, and 10 new core pathways whose effects included inflammatory immunity, apoptosis and nervous system development. The functions of JU group included all functions of JA group, the majority (93.1%) of UA-contributing functions, and 3 new core functions, which focused on physiological system development and function. Conclusion: The pure synergism between UA and JA underlies 10 new core pathways and 3 new core functions, which are involved in inflammation, immune responses, apoptosis and nervous system development.

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Section: Rna Extraction and Microarraymentioning

confidence: 99%

“…The level of statistical significance was set at P<0.05. Finally, canonical pathways with a P value<0.05 and a >1.5-fold change were screened out and analyzed [21][22][23][24][25][26] .…”

Section: Rna Extraction and Microarraymentioning

confidence: 99%

Section: Drug Administrationmentioning

confidence: 99%

Section: Rna Extraction and Microarraymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Phenotype-dependent alteration of pathways and networks reveals a pure synergistic mechanism for compounds treating mouse cerebral ischemia

Wang

et al. 2015

Acta Pharmacol Sin

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Quantitative Identification of Compound‐Dependent On‐Modules and Differential Allosteric Modules From Homologous Ischemic Networks

Liu

et al. 2016

CPT Pharmacometrics Syst. Pharmacol.

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Module‐based methods have made much progress in deconstructing biological networks. However, it is a great challenge to quantitatively compare the topological structural variations of modules (allosteric modules [AMs]) under different situations. A total of 23, 42, and 15 coexpression modules were identified in baicalin (BA), jasminoidin (JA), and ursodeoxycholic acid (UA) in a global anti‐ischemic mice network, respectively. Then, we integrated the methods of module‐based consensus ratio (MCR) and modified Zsummary module statistic to validate 12 BA, 22 JA, and 8 UA on‐modules based on comparing with vehicle. The MCRs for pairwise comparisons were 1.55% (BA vs. JA), 1.45% (BA vs. UA), and 1.27% (JA vs. UA), respectively. Five conserved allosteric modules (CAMs) and 17 unique allosteric modules (UAMs) were identified among these groups. In conclusion, module‐centric analysis may provide us a unique approach to understand multiple pharmacological mechanisms associated with differential phenotypes in the era of modular pharmacology.

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Network‐Wide Screen Identifies Variation of Novel Precise On‐Module Targets Using Conformational Modudaoism

Liu

et al. 2017

CPT Pharmacom & Syst Pharma

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Modular targeting is promising in drug research at the network level, but it is challenging to quantificationally identify the precise on‐modules. Based on a proposed Modudaoism (MD), we defined conserved MD (MDc) and varied MD (MDv) to quantitatively evaluate the conformational and energy variations of modules, and thereby identify the conserved and discrepant allosteric modules (AMs). Compared to the Zsummary, MDc/MDv got an optimized result of module preserved ratio and modular structure. In the mice anti‐ischemic networks, 3, 5, and 1 conserved AMs as well as 4, 1, and 3 on‐modules of baicalin (BA), jasminoidin (JA), and ursodeoxycholic acid (UA) were identified by MDc and MDv, 5 unique AMs and their characteristic actions were revealed. Besides, co‐immunoprecipitation (Co‐IP) experiments validated the representative modular structure. MDc/MDv method can quantitatively define the conformational variations of modules and screen the precise on‐modules network‐wide, which may provide a promising strategy for drug discovery.

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Fusion of core pathways reveals a horizontal synergistic mechanism underlying combination therapy

Cited by 23 publications

References 44 publications

Phenotype-dependent alteration of pathways and networks reveals a pure synergistic mechanism for compounds treating mouse cerebral ischemia

Phenotype-dependent alteration of pathways and networks reveals a pure synergistic mechanism for compounds treating mouse cerebral ischemia

Quantitative Identification of Compound‐Dependent On‐Modules and Differential Allosteric Modules From Homologous Ischemic Networks

Network‐Wide Screen Identifies Variation of Novel Precise On‐Module Targets Using Conformational Modudaoism

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