SELDI蛋白芯片技术筛选脑胶质瘤血清肿瘤标记物的研究
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摘要
目的:筛选胶质瘤患者血清中差异蛋白,建立诊断模型并进行验证;蛋白库中查询、鉴定差异蛋白,探讨其在胶质瘤发病机制中发挥的作用。
方法:对30例胶质瘤患者(治疗前、后组)及12例健康对照者的血清采用表面增强激光解析离子化-飞行时间质谱技术(SELDI-TOF-MS)结合阴离子交换芯片(WCX—2)及蛋白质芯片时间飞行质谱仪进行蛋白质谱分析,运用Biomark Wizard Systerm软件分析血清蛋白组谱,寻找有统计学意义的差异蛋白;运用Biomark PatternSysterm软件分析蛋白质谱,建立胶质瘤诊断模型,并进行验证;在UniProt蛋白数据库中对差异蛋白进行搜索、鉴定,探讨其在胶质瘤发病机制中发挥的作用。
结果:对治疗前胶质瘤组、治疗后胶质瘤组、健康对照组共3组样本进行检测分析,在0～50 000Da范围内经方差分析共得到有高度统计学意义的差异蛋白5个,其中在肿瘤组中呈高表达的有3个,分别为2 235.5±H、3 328.5±H、11 119.8±H Da,肿瘤患者中呈低表达的有2个,分别为7 517.3±H、12 841.7±H Da。对以上5种蛋白的数据在每两组间进行T检验分析,结果11 119.8±H、12 841.7±H Da蛋白含量在胶质瘤治疗后组与健康对照组间差异无统计学意义;2 235.5±H、3 328.5±H Da蛋白含量在这两组间具有统计学意义(P＜0.05);其余蛋白在各组间均有高度统计学差异(P＜0.01)。Biomark Pattern Systerm软件分析并自动选取7 517.3±H、11 119.8±H、12 841.7±H Da建立诊断模型,对胶质瘤治疗前组及健康对照组两组标本进行判别诊断,结果胶质瘤诊断准确性为95.8%(23/24);健康人诊断准确性为100%(12/12);总准确性为97.2%(35/36)。将差异蛋白在UniProt蛋白库查询显示:7 517.3±H Da与PSPHAR对应,其余4种蛋白没有相关对应结果。
结论:本实验运用SELDI-TOF-MS技术在胶质瘤患者血清中共筛选出5种差异蛋白,以此建立的诊断模型能够较为准确地诊断出胶质瘤患者,为SELDI-TOF-MS在胶质瘤临床诊断的应用提供了理论依据;5种差异蛋白中,7 517.3±H Da的蛋白在UniProt蛋白库鉴定为PSPHAR,考虑可能PSPHAR在胶质瘤细胞中表达低下,失去了对细胞周期S期DNA交联、半保留复制的调控,从而对胶质瘤的发生起着十分重要的作用。
Objective:Screening different protein in serum of patients with glioma,set up diagnostic model and to test the model;Identifying the protein in database to explore the pathogenesis of glioma.
Methods:Using surface-enhanced laser desorption ionization-time of flight mass spectrometry (SELDI-TOF-MS) combined with anion exchange chip(WCX-2) and protein-chip time-of-flight mass spectrometer to detect the serum of 30 cases of glioma patients and 12 healthy controls for spectral analysis of proteins;Using the Biomark Wizard Systerm software analysis the protein spectrum of serum,looking for remarkably statistic differences in protein expression;Useing Biomark Pattern Systerm software to analysis protein spectrum to set up the diagnostic model of glioma,and test the model;Identifying the protein in Uniprot protein database to explore the role that the protein played in the pathogenesis of glioma.
Results:5 kinds of protein which had remarkably statistic differences were found in pretherapeutic glioma group,post-therapeutic glioma group,and healthy control group at the range of 0～50 000Da.There were 3 kinds of protein that up-expressed in tumor groups,2235.5±H,3328.5±H, 11119.8±H Da,2 kinds of protein low-expressed,7 517.3±H,12 841.7±H Da.The data of the 5 kinds of protein above-mentioned were analyzed by T test between the each two groups,11 119.8±H, 12 841.7±H Da protein content in post-therapeutic glioma group and the healthy control group had no statistical significance;2 235.5±H,3 328.5±H Da protein between these two groups had statistical significance(P＜0.05);The rest kinds of protein in each group had remarkably statistical significance (P＜0.01).Biomark Pattern Systerm software automatically selected the 7 517.3±H,11 119.8±H,12 841.7±H Da to set up a diagnostic model in order to make diagnosis of glioma.The diagnostic accuracy of the glioma was 95.8%(23/24);and the diagnostic accuracy of healthy was 100% (12/12);the total accuracy was 97.2%(35/36).Protein with MW 7 517.3±H Da was found conforming with SPHAR in UniProt protein database.and the remaining 4 kinds of protein was not related to the corresponding results.
Conclusion.5 kinds of protein which had remarkably statistic differences were found by SELDI-TOF-MS and it could screen biomarkers of glioma efficiently,and the diagnostic model based on this study can be used to diagnose glioma accurately.SPHAR as a DNA crosslinking agents maybe played an important role in the semiconservative synthesis of DNA in S-phase of the cell cycle,and maybe a pathogenic factor of glioma.The remaining 4 kinds of protein was not related to the corresponding results,but they were still important in the pathogenesis of glioma.
方法:对30例胶质瘤患者(治疗前、后组)及12例健康对照者的血清采用表面增强激光解析离子化-飞行时间质谱技术(SELDI-TOF-MS)结合阴离子交换芯片(WCX—2)及蛋白质芯片时间飞行质谱仪进行蛋白质谱分析,运用Biomark Wizard Systerm软件分析血清蛋白组谱,寻找有统计学意义的差异蛋白;运用Biomark PatternSysterm软件分析蛋白质谱,建立胶质瘤诊断模型,并进行验证;在UniProt蛋白数据库中对差异蛋白进行搜索、鉴定,探讨其在胶质瘤发病机制中发挥的作用。
结果:对治疗前胶质瘤组、治疗后胶质瘤组、健康对照组共3组样本进行检测分析,在0～50 000Da范围内经方差分析共得到有高度统计学意义的差异蛋白5个,其中在肿瘤组中呈高表达的有3个,分别为2 235.5±H、3 328.5±H、11 119.8±H Da,肿瘤患者中呈低表达的有2个,分别为7 517.3±H、12 841.7±H Da。对以上5种蛋白的数据在每两组间进行T检验分析,结果11 119.8±H、12 841.7±H Da蛋白含量在胶质瘤治疗后组与健康对照组间差异无统计学意义;2 235.5±H、3 328.5±H Da蛋白含量在这两组间具有统计学意义(P＜0.05);其余蛋白在各组间均有高度统计学差异(P＜0.01)。Biomark Pattern Systerm软件分析并自动选取7 517.3±H、11 119.8±H、12 841.7±H Da建立诊断模型,对胶质瘤治疗前组及健康对照组两组标本进行判别诊断,结果胶质瘤诊断准确性为95.8%(23/24);健康人诊断准确性为100%(12/12);总准确性为97.2%(35/36)。将差异蛋白在UniProt蛋白库查询显示:7 517.3±H Da与PSPHAR对应,其余4种蛋白没有相关对应结果。
结论:本实验运用SELDI-TOF-MS技术在胶质瘤患者血清中共筛选出5种差异蛋白,以此建立的诊断模型能够较为准确地诊断出胶质瘤患者,为SELDI-TOF-MS在胶质瘤临床诊断的应用提供了理论依据;5种差异蛋白中,7 517.3±H Da的蛋白在UniProt蛋白库鉴定为PSPHAR,考虑可能PSPHAR在胶质瘤细胞中表达低下,失去了对细胞周期S期DNA交联、半保留复制的调控,从而对胶质瘤的发生起着十分重要的作用。
Objective:Screening different protein in serum of patients with glioma,set up diagnostic model and to test the model;Identifying the protein in database to explore the pathogenesis of glioma.
Methods:Using surface-enhanced laser desorption ionization-time of flight mass spectrometry (SELDI-TOF-MS) combined with anion exchange chip(WCX-2) and protein-chip time-of-flight mass spectrometer to detect the serum of 30 cases of glioma patients and 12 healthy controls for spectral analysis of proteins;Using the Biomark Wizard Systerm software analysis the protein spectrum of serum,looking for remarkably statistic differences in protein expression;Useing Biomark Pattern Systerm software to analysis protein spectrum to set up the diagnostic model of glioma,and test the model;Identifying the protein in Uniprot protein database to explore the role that the protein played in the pathogenesis of glioma.
Results:5 kinds of protein which had remarkably statistic differences were found in pretherapeutic glioma group,post-therapeutic glioma group,and healthy control group at the range of 0～50 000Da.There were 3 kinds of protein that up-expressed in tumor groups,2235.5±H,3328.5±H, 11119.8±H Da,2 kinds of protein low-expressed,7 517.3±H,12 841.7±H Da.The data of the 5 kinds of protein above-mentioned were analyzed by T test between the each two groups,11 119.8±H, 12 841.7±H Da protein content in post-therapeutic glioma group and the healthy control group had no statistical significance;2 235.5±H,3 328.5±H Da protein between these two groups had statistical significance(P＜0.05);The rest kinds of protein in each group had remarkably statistical significance (P＜0.01).Biomark Pattern Systerm software automatically selected the 7 517.3±H,11 119.8±H,12 841.7±H Da to set up a diagnostic model in order to make diagnosis of glioma.The diagnostic accuracy of the glioma was 95.8%(23/24);and the diagnostic accuracy of healthy was 100% (12/12);the total accuracy was 97.2%(35/36).Protein with MW 7 517.3±H Da was found conforming with SPHAR in UniProt protein database.and the remaining 4 kinds of protein was not related to the corresponding results.
Conclusion.5 kinds of protein which had remarkably statistic differences were found by SELDI-TOF-MS and it could screen biomarkers of glioma efficiently,and the diagnostic model based on this study can be used to diagnose glioma accurately.SPHAR as a DNA crosslinking agents maybe played an important role in the semiconservative synthesis of DNA in S-phase of the cell cycle,and maybe a pathogenic factor of glioma.The remaining 4 kinds of protein was not related to the corresponding results,but they were still important in the pathogenesis of glioma.
引文
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