Profiling of proteins phosphorylated or dephosphorylated during hyperactivation via activation on hamster spermatozoa

Background and Aims  It has been widely accepted that sperm hyperactivation is regulated by protein phosphorylations. But, the sperm hyperactivation phosphorylation pathway is not well understood yet because several different proteins have been detected in other studies. In order to understand the phosphorylation pathway that regulates hyperactivation, we established how to extract sperm protein completely and detected proteins that were phosphorylated during hyperactivation. Methods  Protein phosphorylation of hamster spermatozoa was detected by western blotting using antiphospho-amino acid monoclonal antibodies or the SELDI ProteinChip system with IMAC-Ga(III). Results  We detected 75 protein/peptide phosphoryations using the method established in the present study. Tyrosine phosphorylations occurred during hyperactivation. Serine or threonine phosphorylations occurred for 30 min. Furthermore, four of the serine or threonine phosphorations were phosphorylated by A-kinase. As for peptides, 15 peptides were dephosphorylated for 30 min. Other peptides were phosphorylated during hyperactivation. Conclusions  Because most of the proteins detected in the present study have been described previously, we could detect comprehensive protein phosphorylations. Moreover, we also detected many novel phosphopeptides. Although we did not understand the role of peptide, it was likely that motility was basically regulated by serine/threonine phosphorylations and hyperactivation was mainly regulated by tyrosine phosphorylations. (Reprod Med Biol 2006; 5: 123–135)     

SELDI质谱技术在胰腺癌诊断中的应用进展

胰腺癌是一种高度恶性肿瘤,目前其发病率在国内外均呈上升趋势,而且病死率极高,严重威胁人类健康[1].研究表明,早期发现、早期诊断是有效治疗胰腺癌,提高手术后生存率以及改善预后的关键[2,3].肿瘤发生早期,其蛋白质表达上会出现细微但重要的组合改变[4].     

应用SELDI质谱技术筛选胰腺癌患者的血清标志蛋白

目的:探讨应用SELDI质谱技术对胰腺癌患者血清中特异性标志蛋白的筛选方法。方法:采用表面增强激光解析/离子化飞行时间质谱（SELDI-TOF-MS）技术，选择WCX磁珠及蛋白芯片阅读机对胰腺癌及健康人(对照组)和胰腺良性疾病组的血清进行检测，以筛选胰腺癌患者血清中特异表达差异蛋白。结果:发现胰腺癌血清表达差异的潜在标志物（蛋白）4个，相对分子质量分别为5 705 Da，4 935 Da,5 318 Da和3243 Da，其中4 935 Da，3 243 Da差异表达蛋白质在对照组中低表达，而在胰腺癌组中高表达，5 705 Da和5 318 Da差异表达蛋白质在胰腺癌组中低表达而对照组中高表达。结论:应用SELDI技术筛选胰腺癌患者血清中的特异性生物标记物的方法快速、有效;检测到的4个差异蛋白质可能是胰腺癌患者血清特异性生物标记物。     

SELDI protein profiling of dunning R-3327 derived cell lines: identification of molecular markers of prostate cancer progression

BACKGROUND: We recently demonstrated the protein expression profiling of Dunning rat tumor cell lines of varying metastatic potential (G (0%), AT-1 ( approximately 20%), and MLL (100%)) using SELDI-TOF-MS. As a parallel effort, we have been pursuing the identification of the protein(s) comprising the individual discriminatory "peaks" and evaluating their utility as potential biomarkers for prostate cancer progression. METHODS: To identify the observed SELDI-TOF-MS m/z (mass/charge) values with discriminatory expression between different sublines, we employed a combination of chemical pre-fractionation, liquid chromatography, gel electrophoresis and tandem mass spectroscopy. Identified proteins were then verified by immuno-assay and Western analysis. RESULTS: A 17.5 K m/z SELDI-TOF-MS peak was found to retain discriminatory value in each of two separate study-sets with an increased expression in the metastatic MLL line. Sequence identification and subsequent immunoassays verified that Histone H2B is the observed 17.5 K m/z SELDI peak. SELDI-based immuno-assay and Western Blotting revealed that Histone H2B is specifically over-expressed in metastatic MLL lines. CONCLUSIONS: SELDI-TOF MS analysis of the Dunning prostate cancer cell lines confirmed the consistent overexpression of a 17.5 K m/z peak in metastatic MLL subline. The 17.5 kDa protein from MLL has been isolated and identified as Histone H2B.     

应用SELDI技术建立喉癌患者血清蛋白质指纹图谱筛选模型

背景与目的:建立喉癌患者血清蛋白质指纹图谱筛选模型.材料与方法:用表面加强激光解析/电离飞行时间质谱技术(SELDI-TOF-MS)及WCX2蛋白芯片对33例喉癌患者、30例声带息肉患者血清样本进行分析,将获得的血清蛋白质指纹图谱,用计算机软件进行比较分析,并建立喉癌的筛选模型.结果:喉癌组与声带息肉对照组共有27个蛋白质具有显著性差异;以其中3个蛋白质生物标志物(质/荷比分别为2 779、4 626和5 663)组建的筛选模型检测灵敏度为93.9%,特异性为100%.结论:建立的血清蛋白质指纹图谱模型能够区分喉癌与声带息肉患者,SELDI技术在喉癌的诊断及肿瘤特异性蛋白质生物标志分子的筛选等方面是一种快速而有效的工具.     

SELDI-MS-based expression profiling of ductal invasive and lobular invasive human breast carcinomas

Expression profiling using proteomic techniques has a great potential to identify new biomarkers that might help to better diagnose and treat diseases such as breast cancer, which is one of the leading causes of cancer death in women. Surface-enhanced laser desorption ionization mass spectrometry (SELDI-MS) combines chromatographic separation of peptides and proteins with mass spectrometry and is a fast, user-friendly tool to analyze protein and peptide profiles. SELDI-MS was employed for a comparative analysis of lobular invasive versus ductal invasive breast tumors to find differentially expressed proteins and peptides, and to validate this technique for biomarker identification using complex samples such as tissue. After optimization of sample preparation using HMEC and MCF-7 cell lines, 20 breast tumors were analyzed, and about 550 mass signals corresponding to an estimated 140 native peptides and proteins were detected in each tumor. Only 14% of the mass signals were present in more than six tumors of one subgroup or in more than 12 tumors of both groups showing a great overall heterogeneity of the peptide and protein profiles obtained. Peptide mass signals specific for each of the analyzed groups were identified. In addition, we detected peptides from laser-microdissected ductal invasive and intraductal tumor parts corresponding to peptides present in whole tumors. The low amount of identified peptides and proteins and the observed heterogeneity suggest that SELDI-MS is not well suited for biomarker identification of and profiling experiments on complex samples such as tumor tissue.     

Discovery of distinct protein profiles specific for lung tumors and pre-malignant lung lesions by SELDI mass spectrometry

Objectives: Early lung cancer detection and treatment remain a challenge. The efficacy of surface-enhanced laser desorption/ionization (SELDI) technology in lung cancer detection, has not been defined. This study identifies specific protein peak patterns in malignant lung tumors, and in pre-malignant airways epithelium showing neoplastic transformation. Methods: Lung tumor specimens taken from patients participating in a lung cancer screening study (H. Lee Moffitt Cancer Center, Tampa, FL) were laser capture microdissected to obtain pure cell populations from frozen sections of normal lung, atypical adenomatous hyperplasia (AAH) and malignant tumors. SELDI mass spectrometry was used to generate protein profiles in each epithelial cell type. Results: SELDI mass spectroscopy is highly reproducible in detecting lung tumor-specific protein profiles. Three peaks at 17–23 kDa mass range from tumor cells showed markedly increased compared with normal cells. The peak at 17 250 Da was not detected in any of the normal cells. This peak appeared to be present at low levels in the atypical cell samples. Conclusions: This study demonstrates the feasibility of detecting “malignant” protein signatures from lung tumor and pre-malignant pulmonary epithelium using SELDI mass spectrometry. Although additional study is necessary to validate these patterns as unique diagnostic tools, these “malignant” protein signatures lend themselves to identification of populations at high-risk for lung cancer and for monitoring response to lung cancer chemopreventive agents.     

Classification of pancreatic cystic lesions using SELDI-TOF mass spectrometry

BACKGROUND: The diagnosis of pancreatic cystic lesions is problematical with difficulties arising in the differentiation between malignant, premalignant or benign lesions. This preliminary study aimed to analyse pancreatic cyst fluid, using a proteomic approach, to generate reproducible protein profiles to assist in the classification of malignant and non-carcinoma samples. METHODS: Pancreatic cyst fluid samples from patients with pancreatic adenocarcinoma and non-carcinoma cystic lesions were analysed on hydrophobic protein chip arrays by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). RESULTS: Differential protein expression profiles were observed between pancreatic adenocarcinoma and non-carcinoma cyst fluid samples using SELDI-TOF MS, with 12 protein peaks differentially expressed between pancreatic adenocarcinoma and non-carcinoma. Additionally, unique patterns were observed between the different subtypes of non-carcinoma samples as well as malignant adenocarcinoma. CONCLUSIONS: In this preliminary study we used SELDI-TOF MS to identify protein expression profiles of pancreatic cyst fluid, showing a potential to aid in the differential diagnosis of pancreatic cystic lesions.     

胃癌患者血清比较蛋白质组学研究

目的应用蛋白质质谱分析方法寻找胃癌鉴定的生物标志物。方法应用美国CipherGen公司金属亲和表面(IMAC3)芯片和蛋白芯片仪检测38例胃癌患者、82例正常人血清中的蛋白质相对含量。结果38例胃癌患者与82例正常人在质荷比为1723-14048Da间有18种血清蛋白质含量有显著差异。在学习模式下38例胃癌患者及82例正常人均被正确分组，准确率为100％(120／120)，灵敏度和特异性分别为100％(38／38)、100％(82／82)；在检测模式下38例胃癌患者中有31例被正确论断，82例正常人中有81例被正确分组，灵敏度和特异性分别为81．6％(31／38)、98．8％(81／82)。结论该方法可快速、准确检测胃癌，灵敏度、特异性高。