Search

This study aimed to investigate the molecular mechanism of systemic vasculitis via bioinformatics analysis. Gene express profile of E-GEOD-16945 (13 Takayasu arteritis samples and 13 control samples) was downloaded from European Bioinformatics Institute (EBI) database. Differentially expressed genes (DEGs) were screened between Takayasu arteritis and normal controls (|log FC| > 1). Basic local alignment search tool (BLASTX) was used for the Clusters of Orthologous Groups (COG) classification of DEGs. Gene ontology analysis was performed for the DEGs (P < 0.05). A gene expression network was built with DEGs. Mcode in Cytoscape software was used to extract modules from the network (degree ≥ 2, K-core ≥ 2 and adjusted P-value < 0.05) followed by pathway analysis using GenMAPP (false discovery rate < 0.05). A total of 747 DEGs were identified. There were 16 significant GO function terms enriched with DEGs, of which immune and defence response was the most significant GO term. Totally, three modules were extracted from gene expression network, including one module constituted with upregulated genes and two modules constituted with downregulated genes. Furthermore, human leucocyte antigen (HLA)-DRB1, HLA-DPA1, HLA-DPB1, HLA-DOA and HLA-DRA in the downregulated modules were significantly linked to immune-related pathways (intestinal immune network for IgA production and systemic lupus erythematosus pathways), while ribosomal protein L 31 (RPL31), RPS3A and RPL9 in the upregulated module were enriched in ribosome pathway. The immune-related pathways, ribosome pathway, immune-related genes including (HLA-DRB1, HLA-DPA1, HLA-DPB1, HLA-DOA and HLA-DRA) and ribosome-related genes (RPL31, RPS3A and RPL9) might be involved in systemic vasculitis.

To explore the role of Δ133p53 in the effect of recombinant mutant human Tumor Necrosis Factor (rmhTNF) on two gastric cancer cell lines.MKN45 (with Δ133p53 expression) or SGC7901 (without Δ133p53 expression) cells were treated with rmhTNF of different concentrations only or combined with fluorouracil (5-FU), and the growth inhibition rate was detected by a cell counting kit, and apoptosis by flow cytometry. The mRNA of Δ133p53, p53, Gadd45α, MDM2, PTEN and Bax was measured by reverse transcription PCR (RT-PCR) or Nested PCR (nPCR).On Δ133p53-positive MKN-45 cells, the effect of rmhTNF was significant in growth inhibition test (t = -9.558, p0.01); also, the effect of 5-FU was improved by rmhTNF with remarkable time- and dose-effect (F = 82.742, p0.01; F = 128.583, p0.01). However, on Δ133p53-negative SGC-7901 cells, no growth inhibition was showed by rmhTNF only (t = -0.121, p0.05). In apoptosis test, the effect of rmhTNF was significant on MKN45 cells, and the effect of 5-FU was improved significantly by rmhTNF (F = 123.931, p0.05). In mRNA measurement, rmhTNF-induced up-regulation of p53 accompanied with down-regulation of Δ133p53, which correlated significantly to the change of p53 downstream molecules, including MDM2, PTEN, Gadd45α, and Bax.The results in these experiments suggested that Δ133p53 play a pivotal role in rmhTNF-induced survival of p53 functions in Δ133p53-positive MKN-45 cells.