RESUMEN
OBJECTIVE: To investigate the regulation effects of main active components in Honghua Injection on cerebrovascular disease network. METHODS: Cerebrovascular disease network was constructed using genes from public database RGD based on the protein-protein interaction (PPI) relationship databases HPRD and BioGRID. Then targets of five main active components in Honghua injection was retrieved from PubMed. Component-target relationships were extracted and associated with PPI in cerebrovascular disease. Component-target network was constructed with Cytoscape 3.1.0. Network analysis technologies were applied to find critical targets, biological pathways and potential synergistic effects among components. RESULTS: The component-target network contains 940 nodes and 2360 edges. MCODE analysis extracted 28 clusters in which 18 clusters had at least 3 nodes. There were 6 clusters with score ≥3, and they were further investigated using BinGO analysis. The results showed that the main biological processes included regulation of macromolecule biosynthetic and metabolic processes, neurogenesis, apoptosis, angiogenesis, immune-inflammation reaction, response to hypoxia stress. Our study also indicated that Hydroxysafflor yellow A and Quercetin may show their cerebrovascular-protective potential based on their synergistic anti-apoptosis effects. CONCLUSION: From the view of molecular network, our study applied network pharmacology methods and technologies to reveal the multi-target, multi-pathway mode of action of Honghua injection on anti-cerebro-vascular disease effects, and the synergistic effects among Hydroxysafflor yellow A and quercetin.
RESUMEN
Objective To study the biomarker panel of superficial bladder transitional cell carcinoma(SBTCC)and analyze the biological pathway in tumorigenesis by Shotgun proteomics strategy.Methods Normal urothelium cells and cancer cells were harvested by laser capture microdissection from clinical specimen and the proteomic expression profile was identified by two-dimensional liquid chromatography tandem mass spectrometry.The isoelectric point,molecular weight,grand average of hydropathicity,transmembrane helices were analyzed by using proteomics tools.Gene ontology was used to comment the identified proteins.The pathway analysis was performed by ArrayTrack software,and visualized by GenMAPP.Results There were 440 and 218 proteins expressed in cancer cells and normal cells respectively,among them 388 proteins were differerntially expressed.All the database about identified proteins was deposited in an accessible form to researchers at http://www.Proteome-SBTCC.org.cn and http://www.Proteome-NHTE.org.cn.There were 267(68.8%)differentially expressed proteins which had GO biological process comments.The biological pathwavs of these proteins included MAPK signaling pathway,focal adhesion,oxidative phosphorylation,ECMreceptor interaction,etc.Conclusion Shotgun strategy proteomies database of normal transitional epithelium and SBTCC is successfully constructed.And the basis for the understanding of cell biology and discovery of biomarker panel for SBTCC iS provided.
RESUMEN
Biological pathways are known as collections of knowledge of certain biological processes. Although knowledge about a pathway is quite significant to further analysis, it covers only tiny portion of genes that exists. In this paper, we suggest a model to extend each individual pathway using a microarray expression data based on the known knowledge about the pathway. We take the Rosetta compendium dataset to extend pathways of Saccharomyces cerevisiae obtained from KEGG (Kyoto Encyclopedia of genes and genomes) database. Before applying our model, we verify the underlying assumption that microarray data reflect the interactive knowledge from pathway, and we evaluate our scoring system by introducing performance function. In the last step, we validate proposed candidates with the help of another type of biological information. We introduced a pathway extending model using its intrinsic structure and microarray expression data. The model provides the suitable candidate genes for each single biological pathway to extend it.