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find Author "LIU Qingqing" 2 results
  • Correlation between RUNX3 Expression and Gastric Cancer Risks: A Meta-Analysis

    Objective To investigate the correlation between RUNX3 expression and human gastric cancer, as well as its clinically pathologic features. Methods Such databases as PubMed, EMbase, VIP, WanFang Data and CBM were searched from their inception to February 28th, 2013 to collect case-control studies about the correlation between RUNX3 expression and human gastric cancer, as well as its clinically pathologic features, and the relevant references of the included literature were also retrieved. Two reviewers independently screened the literature according to the inclusion and exclusion criteria, extracted the data, and assessed the methodological quality. Then meta-analysis was conducted using RevMan 5.0 software. Results A total of 6 case-control studies were included, which included 405 cases in the gastric cancer group and 185 cases in the normal gastric mucosa group. The results of meta-analysis showed that, RUNX3 expression was lower in the gastric cancer group than the normal gastric mucosa group, with a significant difference (OR=0.07, 95%CI 0.04 to 0.12, Plt;0.000 01); it was also lower in the subgroup of gastric cancer accompanied with lymph node metastasis than that without lymph node metastasis (OR=0.37, 95%CI 0.23 to 0.61, Plt;0.000 1); but it was higher in the subgroup of gastric cancer that had infiltrated into serosa than that had not, with a significant difference (OR=3.92, 95%CI 2.29 to 6.71, Plt;0.000 01); and it was also higher in the subgroup of well differentiated gastric cancer that the moderately and poorly differentiated, with a significant difference (OR=0.36, 95%CI 0.22 to 0.58, Plt;0.000 1). Conclusion RUNX3 expression is notably correlated to gastric cancer and its clinically pathologic features. For the quantity and quality limitation of the included studies, this conclusion still needs to be further proved by performing more high quality studies.

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  • Identification of hub genes and key pathways in the early therapy of septic shock based on bioinformatics analysis

    Objective To identify potential hub genes and key pathways in the early period of septic shock via bioinformatics analysis. MethodsThe gene expression profile GSE110487 dataset was downloaded from the Gene Expression Omnibus database. Differentially expressed genes were identified by using DESeq2 package of R project. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were constructed to investigated pathways and biological processes using clusterProfiler package. Subsequently, protein-protein interaction (PPI) network was mapped using ggnetwork package and the molecular complex detection (MCODE) analysis was implemented to further investigate the interactions of differentially expressed genes using Cytoscape software. Results A total of 468 differentially expressed genes were identified in septic shock patients with different responses who accepted early supportive hemodynamic therapy, including 255 upregulated genes and 213 downregulated genes. The results of GO and the KEGG pathway enrichment analysis indicated that these up-regulated genes were highly associated with the immune-related biological processes, and the down-regulated genes are involved in biological processes related to organonitrogen compound, multicellular organismal process, ion transport. Finally, a total of 23 hub genes were identified based on PPI and the subcluster analysis through MCODE software plugin in Cytoscape, which included 19 upregulated hub genes, such as CD28, CD3D, CD8B, CD8A, CD160, CXCR6, CCR3, CCR8, CCR9, TLR3, EOMES, GZMB, PTGDR2, CXCL8, GZMA, FASLG, GPR18, PRF1, IDO1, and additional 4 downregulated hub genes, such as CNR1, GPER1, TMIGD3, GRM2. KEGG pathway enrichment analysis and GO functional annotation showed that differentially expressed genes were primarily associated with the items related to cytokine-cytokine receptor interaction, natural killer cell mediated cytotoxicity, hematopoietic cell lineage, T cell receptor signaling pathway, phospholipase D signaling pathway, cell adhesion molecules, viral protein interaction with cytokine and cytokine receptor, primary immunodeficiency, graft-versus-host disease, type 1 diabetes mellitus. Conclusions Some lymphocytes such as T cells and natural killer cells, cytokines and chemokines participate in the immune process, which plays an important role in the early treatment of septic shock, and CD160, CNR1, GPER1, and GRM2 may be considered as new biomarkers.

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