School of Pharmacy and Biomedical Sciences, University of Portsmouth, Portsmouth, PO1 2DT, Hampshire, U.K.
Cancer Genomics Proteomics. 2010 Mar-Apr;7(2):93-103.
The incidence of prostate cancer (PCa) has increased in recent years due to the aging of the population and increased testing; however, mortality rates have remained largely unchanged. Studies have shown deficiencies in predicting patient outcome for both of the major PCa diagnostic tools, namely prostate specific antigen (PSA) and transrectal ultrasound-guided biopsy. Therefore, serum biomarkers are needed that accurately predict prognosis of PCa (indolent vs. aggressive) and can thus inform clinical management.
This study uses surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) mass spectrometry analysis to identify differential serum protein expression between PCa patients with indolent vs. aggressive disease categorised by Gleason grade and biochemical recurrence.
A total of 99 serum samples were selected for analysis. According to Gleason score, indolent (45 samples) and aggressive (54) forms of PCa were compared using univariate analysis. The same samples were then separated into groups of different recurrence status (10 metastatic, 15 biochemical recurrences and 70 non-recurrences) and subjected to univariate analysis in the same way. The data from Gleason score and recurrence groups were then analysed using multivariate statistical analysis to improve PCa biomarker classification.
The comparison between serum protein spectra from indolent and aggressive samples resulted in the identification of twenty-six differentially expressed protein peaks (p<0.05), of which twenty proteins were found with 99% confidence. A total of 18 differentially expressed proteins (p<0.05) were found to distinguish between recurrence groups; three of these were robust with p<0.01. Sensitivity and specificity within the Gleason score group was 73.3% and 60% respectively and for the recurrence group 70% and 62.5%.
SELDI-TOF-MS technology has facilitated the discovery of prognostic biomarkers in serum that can successfully discriminate aggressive from indolent PCa and also differentiate between recurrence groups.
由于人口老龄化和检测增加，近年来前列腺癌（PCa）的发病率有所增加；然而，死亡率基本保持不变。研究表明，前列腺特异性抗原（PSA）和经直肠超声引导活检这两种主要的 PCa 诊断工具在预测患者预后方面都存在不足。因此，需要能够准确预测 PCa（惰性与侵袭性）预后的血清生物标志物，从而为临床管理提供信息。
本研究使用表面增强激光解吸/电离飞行时间质谱（SELDI-TOF-MS）质谱分析来鉴定前列腺癌患者中具有惰性和侵袭性疾病的血清蛋白表达差异，这些患者根据 Gleason 分级和生化复发进行分类。
共选择了 99 个血清样本进行分析。根据 Gleason 评分，使用单变量分析比较了具有惰性（45 个样本）和侵袭性（54 个样本）形式的 PCa。然后，将相同的样本分为不同复发状态的组（10 个转移性、15 个生化复发和 70 个无复发），并以相同的方式进行单变量分析。然后使用多变量统计分析来分析 Gleason 评分和复发组的数据，以提高 PCa 生物标志物的分类。
将来自惰性和侵袭性样本的血清蛋白谱进行比较，结果鉴定出 26 个差异表达的蛋白峰（p<0.05），其中 20 个蛋白具有 99%的置信度。还发现 18 个差异表达蛋白（p<0.05）可以区分复发组；其中 3 个蛋白具有很强的区分能力（p<0.01）。在 Gleason 评分组内的敏感性和特异性分别为 73.3%和 60%，在复发组内分别为 70%和 62.5%。
SELDI-TOF-MS 技术促进了血清中预后生物标志物的发现，这些标志物可以成功地区分侵袭性和惰性 PCa，还可以区分复发组。
