目的探讨肾移植后急性排斥反应中炎症相关因子的表达变化及蛋白网络的功能。方法收集肾移植后急性排斥反应患者及肾功能稳定患者血清样本,各6例;应用APIX蛋白芯片技术检测40个炎症相关细胞因子,寻找两组间表达水平差异具有统计学意义的细胞因子。并应用String和Network OntologyAnalysis在线工具构建差异蛋白相互作用网络,分析其生物功能。结果在急性排斥反应及肾功能稳定患者的血清中有8个细胞因子的表达水平差异有统计学意义[嗜酸细胞活化趋化因子2(CCL24):700(255~1157)比330(100~610)rig/L;细胞间黏附分子1(ICAM.1):58737(8018—105395)比22660(137~68914)ng/L;白细胞介素10(IL一10):120(20~517)比298(81~11609)ng/L;IL-6可溶性受体(IL-6sR):11328(3357~21251)比7665(370~12455)-s/L;单核细胞炎性蛋白10α(CCL3):1712(7002~32634)比283(54—1915)ng/L;单核细胞炎性蛋白1B(CCIA):554(28~2355)和283(104~1915)ng/L;基质金属蛋白酶组织抑制因子1(TIMP.1):15560(13343~42481)比11271(1207~18228)ng/L;正常T细胞表达和分泌因子(CCL5):44547(38252~78631)比27765(12073~46627)ng/L,均P〈0.05]。蛋白相互作用及网络分析显示这些蛋白彼此联系,参与趋化、化学趋化、炎症反应、创伤应答及白细胞迁移等病理生理过程。结论寻找肾移植急性排斥反应患者差异表达的炎症相关细胞因子并分析蛋白相互作用网络,有助于阐明肾移植急性排斥反应发病机制;差异蛋白可作为肾移植急性排斥反应候选诊断标志物或干预靶标。
Objective To explore the changes of inflammation cytokines during acute renal transplantation rejection and decipher the functions of their protein-protein interaction network. Methods Serum samples were collected from renal transplantation patients with stable renal function or acute rejection (n = 6 each ) to measure the expression level of 40 inflammatory factors by APIX protein array. The differentially expressed proteins were selected and their protein-protein interaction networks constructed. And biologic processes were analyzed by the online tools of String and Network Ontology Analysis. Results There were 8 differentially expressed cytokines in the AR group versus the stable group(M (Q1 -Qs ), CCL24:700 (255 -l157)vs 330(100 -610)ng/L,ICAM-1:58 737 (8018 -105 395) vs 22 660 (137 -68 914) ng/L, IL-10:120(20 - 517) vs 298 (81 - 11 609) ng/L,IL-6sR:ll 328(3357 -21 251 ) vs 7665(370 - 12 455) ng/L, CCL3:1712(7002 -32 634) vs 283(54 - 1915) ng/L,CCIA :554 (28 -2355) vs 283 ( 104 - 1915) ng/L, TIMP-1 : 15 560 ( 13 343 - 42 481 ) vs 11 271 ( 1207 - 18 228) ng/L, CCL5 : 44 547 (38 252 - 78 631 ) vs 27 765 ( 12 073 - 46 627 ) ng/L, all P 〈 0. 05 ). The analyses of protein-protein association network showed that these proteins were correlated and involved in such biological processes as taxis, chemotaxis, inflammatory reactions, wound responses and leukocytic migration. Conclusions Comparing the inter-group differences of inflammatory cytokines and further developing and analyzing the protein-protein interaction network may help us to explore the mechanisms of acute renal transplantation rejection. And the differential cytokines can be used as candidate diagnostic biomarkers and intervention targets.