应用蛋白质芯片技术筛选人舌鳞癌细胞株差异性炎症因子的初步研究

目的研究应用蛋白质芯片(抗体芯片)技术筛选、分析人舌鳞状细胞癌细胞株中差异性炎症因子的效果,为进一步探讨口腔癌与炎症的关系奠定基础。方法体外培养人舌鳞癌细胞株UM-1、CAL-27、Tca-8113和人正常口腔黏膜上皮细胞,消化后分别提取胞内、胞外蛋白,上芯片孵育,封闭,清洗。采用激光扫描仪扫描芯片,Axon GenePix Pro6.0软件提取芯片数据,对获得的80种炎症因子表达数据采用AAH-CYT-G5软件分析,上调因子信号值以大于200、比值大于2.0为纳入标准;下调因子信号值以大于200、比值小于0.66为纳入标准,分别对3种人舌鳞癌细胞株(UM-1、CAL-27、Tca-8113)与人正常口腔黏膜上皮细胞,以及高侵袭性细胞株(UM-1、CAL-27)与低侵袭性细胞株(Tca-8113)进行两两比较,筛选出差异性炎症因子。挑选3种显著差异性炎症因子,用酶联免疫吸附法再次检测其蛋白表达,所得结果用单因素方差分析进行统计学分析,进一步验证芯片法所获得的结果。结果根据纳入标准,从检测的80种因子中筛选出有表达的炎症因子9个,包括干扰素诱导蛋白10(inter-feron inducible protein10,IP-10)、巨噬细胞炎症蛋白-1β(macrophage inflammatory protein1β,MIP-1β)、巨噬细胞炎症蛋白-3α(macrophage inflammatory protein-3α,MIP-3α)、骨保护素蛋白(osteoprotegerin,OPG)、调节活化蛋白(regulated upon activation normal T-cell expressed and secreted,RANTES)、白细胞介素1β(interleukin1β,IL-1β)6种舌鳞癌细胞株中高表达的细胞因子,及单核细胞趋化因子4(monocyte chemoattractant protein4,MCP-4)、胰岛素样生长因子结合蛋白4(insulin-like growth factor binding protein-4,IGFBP-4)、转化生长因子-β3(transforminggrowth factor-β3,TGF-β3)3种舌鳞癌细胞株中低表达的细胞因子。鳞状细胞癌细胞和正常口腔鳞状上皮细胞之间比较,胞内IL-1β呈高表达,MCP-4呈低表达,胞外OPG呈高表达;高、低侵袭性细胞株之间比较,胞内RANTES呈高表达,IGFBP-4、TGF-β3呈低表达,胞外IP-10、MIP-1β、MIP-3α呈高表达。酶联免疫吸附法检测发现UM-1和CAL-27胞外IP-10、MIP-1β、MIP-3α的表达量和Tca-8113相比呈高表达,差异有统计学意义(P<0.05)。其结果与芯片筛选结果一致。结论蛋白质芯片技术能够较为准确地筛选出不同舌鳞癌细胞株之间差异性炎症因子,这些差异性炎症因子可能与肿瘤细胞的生物学行为有一定的联系。

Screening of inflammatory cytokine expression in different human tongue squamous cell carcinoma cell lines using cytokine antibody arrays

Objective To identify and analyse the different expression and significance of inflammatory cytokine of tongue squamous cell carcinoma cell lines using protein chip （antibody arrays）. Methods Cultured tongue cancer cells CAL-27, UM-1, Tca-8113 and human oral epithelial cells in vitro, extracted extracellular and intracellular proteins, after digestion respectively. Then handled these on the glass chips with clean, blocking, and incubation, and thenadopted the laser scanner GenePix 4000B to scan the chip, the software Axon GenePix Pro 6.0 to extract the chip data, and the software AAH-CYT-G5 to analyse the expression data of 80 obtained kinds of cell inflammatory cytokines. The upregulation of cytokine signal value was greater than 200, greater than 2.0 cytokine in ratio as the inclusion criteria, and the down-regulation of cytokine signal value was greater than 200, less than 0.66 cytokine in ratio as the inclusion criteria. The data was analyzed by Pairwise comparison between tongue squamous cell carcinoma cell lines （UM-1, CAL-27, TCA-8113） and human normal oral mucosa epithelial cells, and between high invasive cell lines （UM-1, CAL-27） and low invasive cell lines （TCA-8113）. And then choosed the different cytokines, including 3 kinds of different significant inflammatory cytokine. Using ELISA to re-detect the expression of the protein, the obtained result from the re-detection were proceeded the statistical analysis, for the futher confirm of the antibody array results. Results According to the inclusion criteria, 9 expressed inflammatory cytokines were choosed from the 80 kinds of detected cytokines, including screened 6 high-expressed cytokines in tongue squamous cell carcinoma cell lines such as IP-10, MIP-1β, MIP-3α, Osteoprotegerin, RANTES, IL-1β, et al, as well as 3 low-expressed cytokines in tongue squamous cell carcinoma cell lines such as cytokines MCP-4, IGFBP-4, TGF-β3. Compared human normal oral mucosa epithelial cells with squamous cell carcinoma, IL-1β in intracellular sample expressed higher, and MCP-4 expressed lower, Osteoprotegerin in extracellular sample expressed higher. Compared with high and low invasive cell lines, RANTES in intracellular sample expressed higher, GFBP-4,TGF-β3 expressed lower, and IP-10,MIP-1β,MIP-3α in extracellular sample expressed higher. The expression quantity of CAL-27 and UM-1 by ELISA, and IP-10, MIP-1β, and MIP-3α in extracellular sample expressed higher, comparing to Tca-8113. There was a significant difference in statistics （P〈0.05）. The results were consistent with chip screening. Conclusion The results demonstrated that different cytokines expression in different tongue cancer cell lines could be relatively accurately screened via cytokine antibody array technology, and these cytokines might have certain connections with tongue cancer cell biological behaviors.