Skytt Asa, Thysell Elin, Stattin Pär, Stenman Ulf-Håkan, Antti Henrik, Wikström Pernilla
Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden.
Int J Cancer. 2007 Aug 1;121(3):615-20. doi: 10.1002/ijc.22722.
There is an urgent need for better biomarkers for detection of clinically significant prostate cancer (PCa). Recent studies suggest that surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) analysis of serum may provide diagnostic information. The aim of this study was to investigate if PCa cases could be identified by applying predefined SELDI-TOF analysis conditions on prospectively, uniformly collected plasma samples from PCa cases and matched controls. Prospective samples from 387 incident PCa cases and an equal number of controls, matched for age and time for recruitment, were analyzed by SELDI-TOF MS (IMAC30/Cu chip) and multivariate classification analysis. Prospective prostate specific antigen levels were subjected to ROC curve analysis giving an AUC of 0.87 for the total cohort with a median lag time between blood sampling and diagnosis of 6.1 years. No markers were found by SELDI-TOF MS that significantly discriminated between cases and controls in the total cohort or in subanalysis of cases with less than 2 years between blood donation and diagnosis (n = 42). Cases with aggressive disease at the time of diagnosis who gave blood less than 4 years prior to diagnosis (n = 23) could however be separated from their controls (sensitivity 70%, specificity 83%) by a model based on SELDI-TOF MS and OPLS-DA data analysis. We were thus not able to confirm previous results with SELDI-TOF MS identifying men with PCa from healthy individuals, but we report an optimal experimental set-up for verification of markers for early detection of cancer in prospectively collected samples.
迫切需要更好的生物标志物来检测具有临床意义的前列腺癌(PCa)。最近的研究表明,血清表面增强激光解吸/电离飞行时间质谱(SELDI-TOF MS)分析可能提供诊断信息。本研究的目的是调查是否可以通过对来自PCa病例和匹配对照的前瞻性、统一收集的血浆样本应用预定义的SELDI-TOF分析条件来识别PCa病例。通过SELDI-TOF MS(IMAC30/Cu芯片)和多变量分类分析,对387例新发PCa病例和数量相等的对照(年龄和招募时间匹配)的前瞻性样本进行了分析。对前瞻性前列腺特异性抗原水平进行ROC曲线分析,整个队列的AUC为0.87,采血与诊断之间的中位滞后时间为6.1年。在整个队列中或在献血与诊断间隔小于2年的病例亚分析(n = 42)中,未发现SELDI-TOF MS能够显著区分病例和对照的标志物。然而,对于诊断时患有侵袭性疾病且在诊断前4年内献血的病例(n = 23),基于SELDI-TOF MS和OPLS-DA数据分析的模型可以将其与对照区分开来(敏感性70%,特异性83%)。因此,我们无法证实之前利用SELDI-TOF MS从健康个体中识别出PCa患者的结果,但我们报告了一种用于在前瞻性收集的样本中验证癌症早期检测标志物的最佳实验设置。