Okamoto Akiko, Yamamoto Hayato, Imai Atsushi, Hatakeyama Shingo, Iwabuchi Ikuya, Yoneyama Takahiro, Hashimoto Yasuhiro, Koie Takuya, Kamimura Noritaka, Mori Kazuyuki, Yamaya Kanemitsu, Ohyama Chikara
Department of Urology, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Oncol Rep. 2009 Jan;21(1):73-9.
Post-prostatic massage urine specimens (PMUS) are expected to be rich in proteins originating from the prostatic acini. In this study, we created a PMUS bank consisting of 57 samples obtained from patients with biopsy-proven prostate cancer (PC) and 56 samples from subjects with biopsy-proven benign lesions to analyze protein profiles of PMUS by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Strong anion-exchange (Q10), weak cation-exchange (CM10) and immobilized metal affinity capture (IMAC30) ProteinChip Arrays were used for protein profiling. In PC samples, single-marker analysis detected 49 mass peaks that were significantly up-regulated and 23 peaks that were significantly down-regulated, compared with peaks obtained from benign lesion samples. To confirm reproducibility we performed additional three rounds of assay using CM10 chip with pH 4.0 binding buffer. Among these significant peaks, a peak of m/z 10788 was significant throughout all 4 rounds of assays. For hierarchical clustering analysis (HCA), we used the 72 peaks which revealed significant differences in single-marker analysis. The heat map discriminated PC from benign lesions with a sensitivity of 91.7% and a specificity of 83.3%. Therefore, SELDI-TOF MS profiling of PMUS can be applied to differentiate patients with PC from cancer-free subjects. However, further investigation is required to verify the usefulness of this method in clinical practice.
前列腺按摩后尿液样本(PMUS)预计富含源自前列腺腺泡的蛋白质。在本研究中,我们创建了一个PMUS库,其中包括57份来自经活检证实患有前列腺癌(PC)患者的样本和56份来自经活检证实患有良性病变受试者的样本,以通过表面增强激光解吸/电离飞行时间质谱(SELDI-TOF MS)分析PMUS的蛋白质谱。使用强阴离子交换(Q10)、弱阳离子交换(CM10)和固定化金属亲和捕获(IMAC30)蛋白质芯片阵列进行蛋白质谱分析。在PC样本中,与良性病变样本获得的峰相比,单标记分析检测到49个显著上调的质量峰和23个显著下调的峰。为了确认可重复性,我们使用pH 4.0结合缓冲液的CM10芯片进行了另外三轮检测。在这些显著峰中,m/z 10788的峰在所有四轮检测中均显著。对于层次聚类分析(HCA),我们使用了在单标记分析中显示出显著差异的72个峰。热图区分PC和良性病变的灵敏度为91.7%,特异性为83.3%。因此,PMUS的SELDI-TOF MS谱分析可用于区分患有PC的患者和无癌受试者。然而,需要进一步研究以验证该方法在临床实践中的实用性。