MALDI-TOF质谱技术在肺癌中的应用

基质辅助激光解析电离飞行时间质谱（MALDI-TOF-MS）是一种新型的质谱技术,具有高通量、快速、重复性好、灵敏性高等优点,是目前肺癌研究与临床应用的重要工具,在肺癌早期诊断、筛查、疗效评价等方面有着良好的应用前景.     

新的肺癌血清标志物——甲状腺运载蛋白

背景与目的 肺癌是当今世界上最常见的恶性肿瘤之一,迄今缺乏临床诊断可用的分子标志物.本实验应用SELDI技术寻找肺癌新的血清标志物.方法 对227例血清样品(包括146例肺癌、13例肺炎、28例结核性胸膜炎和40例正常人血清样品)进行蛋白质谱检测.对候选蛋白进行质谱鉴定,并结合免疫共沉淀和ELISA技术筛选出肺癌新的候选标志物.结果 通过Biomarker WizardTM软件分析显示13.78 kDa、13.90 kDa和14.07 kDa的蛋白峰在肺癌病人血清样品中明显低于对照组.通过1-D胶分离,质谱鉴定和免疫沉淀分析显示这3个差异蛋白峰为野生型甲状腺运载蛋白(nativeTTR)和它的两个变体(cysTTR and glutTTR).ELISA和SELDI技术分析上述血清样品均发现TTRs在肺癌血清中的表达下调.结论 采用SELDI技术首次筛选并鉴定出TTRs,表明其可能作为肺癌诊断的候选血清标志物.     

蛋白质组学及其研究技术在肺癌分子生物标志物研究中的应用

肺癌是全球发病率和死亡率较高的恶性肿瘤。细胞从正常状态转变为肿瘤的过程中，细胞内蛋白质表达谱必然会发生一系列变化，肿瘤分子标记物就是细胞在非正常状态下产生的分子．以高通量结合生物信息学为特点的蛋白质组学分析技术可以从细胞整体水平上检测到这种变化近年来，为了降低肺癌的死亡率并提高其治疗效果，研究人员利用这一新的手段如利用激光捕获显微切割技术和双相凝胶电泳结合基质辅助激光解析电离飞行时间质谱（MALDI-TOF MS）和表面增强激光解析电离色行时间质谱（SELDI—TOF MS）寻找有效的肺癌标记物。本文对蛋白质组学技术在肺癌生物标志物研究中的应用作了综述。     

应用SELDI—TOF—MS技术于肺癌中医辩证的初步研究

目的 探讨不同证型肺癌患者血清中蛋白质质谱的差异.方法 用WCX2蛋白芯片结合表面增强激光解析电离飞行时间质谱(SELDI-TOF-MS)技术,分别检测12例气阴两虚肺癌和12例气滞血淤肺癌的血清蛋白质谱,筛选出差异表达蛋白质.结果 共检测到113个有效的蛋白质波蜂,其中m/z位于2 000-10 000的波峰有104个,筛选出m/z为3 952.05、3 772.35、4 170.07、3 679.34、3 156.38、4 293.14的6个血清蛋白质.结论 利用SELDI-TOF-MS技术将有可能建立新的中医肺癌辩证模式--蛋白质指纹图谱.     

肺癌分子预后分析

在肺癌的临床研究中，预后分析是分期的主要目标之一，也是制定治疗方案的重要依据。通过对肺癌原发肿瘤、淋巴结、血液和骨髓的检查，从基因或蛋白质水平进行分子预后分析，进而进行肺癌分子分期（molecular staging of lung cancer）。将把肺癌分期的准确性提高到一个新的水平。分子预后分析研究的内容主要是基因扩增、基因突变、基因产物过度表达／异常表达、限制性酶切片段长度多态性分析以及微卫星不稳定性分析。主要的技术方法包括免疫组化染色技术、酶联免疫吸附实验（ELISA）、逆转录聚合酶链反应（RT—PCR）、蛋白质印迹（western blot）、染色体分析、等位基因特异性寡核营酸分析法（ASO）、芯片技术及质谱分析（MS）等。     

肺癌骨转移相关分子的比较蛋白质组学研究

目的:分析比较人肺癌不同骨转移潜能细胞株的差异表达蛋白质图谱,筛选在肺癌骨转移中起重要作用的关键蛋白质分子。方法:利用双向凝胶电泳(2-DE)和基质辅助激光解析离子化-飞行时间-质谱技术,分析人肺癌骨转移细胞株SBC-5和非骨转移细胞株SBC-3/DOX蛋白质图谱的差异表达,查询数据库筛选肺癌骨转移相关蛋白质。结果:PDQuest 8.0软件分析3次相同条件下的2-DE图谱,结果显示重复性、匹配性较好。SBC-5检测到(1116±64)个蛋白点,平均匹配率为84%;SBC-3/DOX检测到(1132±72)个蛋白点,平均匹配率为82%;蛋白质点分布以PI 4-7、相对分子质量20 000-80 000范围内最多。两种细胞株16个差异蛋白质点胰酶胶内酶解,质谱分析获得14张肽质量指纹谱,鉴定出Annexin A1,CaN,IGFBP-1,ADAM32等8种胶内差异蛋白质。结论:人肺癌不同骨转移潜能细胞株SBC-5和SBC-3/DOX的2-DE蛋白质图谱具有明显的差异表达,多种差异表达蛋白可能与肺癌骨转移相关。     

肺癌骨转移血清蛋白质组学研究

目的:应用蛋白质组学双向荧光差异凝胶电泳和质谱技术筛选肺癌骨转移血清标志.方法:收集肺癌伴骨转移、无骨转移各24例血清样本.同组血清等量混合,用除白蛋白试剂盒除去血清中的白蛋白,再经除盐浓缩后,将4组处理后的血清样品用不同的CyDye染料交叉标记后进行双向荧光差异凝胶电泳(2-D DIGE).利用DeCyder软件分析,将肺癌伴骨转移组与肺癌无骨转移组比较的差异蛋白质点行基质辅助激光解析离子化飞行时间质谱(MALDI-TOF-MS)鉴定.结果:双向荧光差异凝胶电泳显示,肺癌骨转移组血清蛋白中有16个斑点,与肺癌无骨转移组相比差异有统计学意义.其中11个蛋白质表达水平显著增加,选取5个蛋白质表达水平显著下降.5个差异蛋白点进行胶内原位酶解、肽质指纹图谱分析,成功得到4个蛋白质肽质指纹图,并查询数据库初步鉴定该4个蛋白质分别为视黄醇结合蛋白-甲状腺素运载蛋白复合物(RBP-TTR)、结合殊蛋白(Hp)、S-亚硝基血红蛋白(SNO-Hb)和de-sArg141 α Hb.结论:双向荧光差异凝胶电泳结合质谱鉴定是血清差异蛋白质组学研究的可靠平台和有力工具.所鉴定出的蛋白质可能与肺癌骨转移的发生、发展有关,有助于肺癌骨转移发病机制的了解.     

气管、肺（080146～080231）

武汉市城区居民肺癌危险因素的研究；重组腺病毒TRAIL基因联合抗EGFR靶向药物对肺癌细胞增殖的影响；非小细胞肺癌放化疗患者血清蛋白质谱分析的初步研究；99m^Tc-MIBI肺肿瘤显像与MRP表达的关系；CBP基因在非小细胞肺癌中的表达及其生物学意义。     

蛋白质组学方法筛选早期肺鳞癌相关蛋白

目的:应用蛋白质组学技术筛选早期肺癌癌变相关蛋白.方法:利用双向凝胶电泳方法分离人早期肺鳞癌组织和相应癌旁正常组织总蛋白,选择差异蛋白质点进行质谱分析.免疫组织化学法验证部分差异蛋白质的表达差异.结果:肺鳞癌组织与癌旁正常组织的双向凝胶电泳图谱中平均蛋白质点数分别为626和602个.选择在癌组织中高表达的10个差异蛋白点进行质谱分析,最终鉴定为膜联蛋白1 (annexin-1, Anx-A1)、热休克蛋白27(heat shock protein 27, HSP27)等与细胞周期、信号转导等功能相关的蛋白质.免疫组织化学检测结果显示,Anx-A1和HSP27蛋白在肺鳞癌组织中的阳性表达率均显著增高(P<0.05).结论:蛋白质组学方法是一种应用于初步筛选早期肺癌相关蛋白的有效方法,所鉴定的蛋白为进一步筛选用于肺癌早期诊断及其治疗的分子标志物奠定了前期基础.     

肿瘤标志物蛋白芯片检测系统在肺癌诊断中的价值

近年来肺癌的发病率和死亡率都有所上升，是严重危害人们身体健康的恶性肿瘤之一，因此肺癌的早期诊断至关重要。蛋白芯片是近年来在生命科学领域中迅速发展起来的高新科技，主要通过微加工技术和微电子技术在固体芯片表面构建微型生物化学分析系统对肿瘤标志物进行检测，从而为肺癌的辅助诊断提供重要的根据。本实验采用蛋白芯片对188例肺癌患者进行多项肿瘤标志物的检测，探讨其在肺癌诊断中的价值。     

飞行质谱技术在早期消化道肿瘤研究的应用现状

目的:综述飞行质谱技术在早期消化道肿瘤研究中的应用。方法:以"癌前病变、蛋白质组学、飞行时间质谱、肿瘤、肿瘤标志"为关键词,运用pubMed central及CNKI期刊全文数据库检索2000-2011有关文献,初步筛选150余篇相关文献,纳入标准:1)消化道肿瘤相关流行病学调查现状;2)飞行时间质谱在食管癌、胃癌及大肠癌早期中的研究现状。根据纳入标准,纳入分析26篇相关文献。结果:大量研究结果证明飞行时间质谱技术的灵敏度及特异性均>85%,能够发现早期肿瘤组织或体液当中传统技术所不能发现的差异蛋白改变,为消化道肿瘤的发生发展、早期诊断及临床筛查提供新的途径。结论:质谱技术将成为早期消化道肿瘤蛋白变化研究的主要技术之一。     

Fibrinogen gamma overexpression in pancreatic cancer identified by large-scale proteomic analysis of serum samples

Detection of serum markers for pancreatic cancer has been elusive. Although CA 19-9 is most commonly used, its sensitivity and specificity are modest. We used large-scale proteomics to identify potential serum markers for pancreatic cancer. Samples were analyzed using high-resolution two-dimensional gel electrophoresis to identify differentially expressed proteins in 32 normal and 30 pancreatic cancer patients. Up to 1,744 protein spots were resolved for each serum sample. Candidate proteins were identified using mass spectrometry. ANOVA was used to identify proteins that could discriminate cancer from normal sera. Serum fibrinogen level was also measured using enzymatic assay. Immunohistochemistry was used to detect fibrinogen in resected pancreatic cancers. One hundred fifty-four proteins were commonly overexpressed in all pancreatic cancers. Nine protein spots (four with identifications by mass spectrometry) could effectively separate cancer from normal controls using cross-validation. These proteins successfully discriminated all pancreatic cancer samples (30 of 30) and 94% of normal (30 of 32) samples. Prominent among these candidates was fibrinogen gamma, which was subsequently confirmed to be overexpressed in pancreatic cancer sera by enzymatic analysis (54.1 +/- 64.1 versus 0.0 +/- 0.0 mg/dL, P < 0.05) and tissue by immunohistochemistry (67% versus 29%, P < 0.05) relative to normal pancreas. Proteomic analysis combining two-dimensional gel electrophoresis and mass spectrometry successfully identified 154 potential serum markers for pancreatic cancer. Of these, fibrinogen gamma, a protein associated with the hypercoagulable state of pancreatic cancer, discriminated cancer from normal sera. Fibrinogen is a potential tumor marker in pancreatic cancer.     

乳腺癌的蛋白质组学研究

乳腺癌蛋白质组学研究手段众多,尤其以质谱技术发展较快.随着研究的深入,乳腺癌诊断和预后的特异性标志物不断被发现,对指导乳腺癌的临床诊疗和预后判断具有重要意义.     

蛋白芯片表面增强激光解吸电离-飞行时间-质谱技术在肿瘤早期诊断中的

 蛋白质芯片表面增强激光解吸电离-飞行时间-质谱（surface enhanced laser desorp-tion/ionization time of flight mass spectrometry, SELDI-TOF-MS）技术是近年发展起来的蛋白质组学研究的新技术，在各种肿瘤的早期诊断和研究中，具有广阔的发展前景及临床意义。就其技术原理、组成、在肿瘤早期诊断中的运用及发展前景作一综述。     

蛋白质组学在乳腺癌研究中的应用

蛋白质组学在肿瘤研究中的应用是近几年的研究热点,许多新方法也不断应用于蛋白质组学的研究中,包括组织芯片、蛋白质芯片、差异显示双相凝胶电泳以及最新的表面增强激光解析电离飞行时间质谱(SELDI-TOF-MS)蛋白质芯片技术,这些新方法在乳腺癌的早期诊断、预后评价以及信号转导等方面都取得一定进展。     

蛋白质组学在乳腺癌研究中的应用

蛋白质组学在肿瘤研究中的应用是近几年的研究热点,许多新方法也不断应用于蛋白质组学的研究中,包括组织芯片、蛋白质芯片、差异显示双相凝胶电泳以及最新的表面增强激光解析电离飞行时间质谱（SELDI-TOF-MS）蛋白质芯片技术,这些新方法在乳腺癌的早期诊断、预后评价以及信号转导等方面都取得一定进展。     

Detection of breast cancer biomarkers in nipple aspirate fluid by SELDI-TOF and their identification by combined liquid chromatography-tandem mass spectrometry

Screening mammography is the most effective tool available for breast cancer detection. While screening mammography saves lives, it has intrinsic problems that limit further improvement. We hypothesize that protein biomarkers in nipple aspirate fluid (NAF) may separate the cancer from the non-cancer state, and therefore can be used for breast cancer detection. In this study the proteins in NAF were analyzed by surface-enhanced laser desorption ionization coupled to time-of-flight mass spectrometry (SELDI-TOF) in the m/z 5,000-85,000 range. Two methods were used to normalize spectra. Then differentially expressed signals that separate cancer from non-cancer conditions were selected by two specifically developed statistical algorithms. Proteins of interest were identified by combined liquid chromatography-tandem mass spectrometry. A set of 8 markers were identified which collectively gave 63% sensitivity, 89% specificity and 76% accuracy for distinguishing cancer from non-cancer. Further improvements in the specificity and sensitivity of this strategy could come from the development of methods for more precise quantification of the biomarkers of interest and also from focusing on the low abundant components that are not evident when unfractionated NAF is analyzed directly.     

Proteomic biomarkers in lung cancer

The correct understanding of tumour development relies on the comprehensive study of proteins. They are the main orchestrators of vital processes, such as signalling pathways, which drive the carcinogenic process. Proteomic technologies can be applied to cancer research to detect differential protein expression and to assess different responses to treatment. Lung cancer is the number one cause of cancer-related death in the world. Mostly diagnosed at late stages of the disease, lung cancer has one of the lowest 5-year survival rates at 15 %. The use of different proteomic techniques such as two-dimensional gel electrophoresis (2D-PAGE), isotope labelling (ICAT, SILAC, iTRAQ) and mass spectrometry may yield new knowledge on the underlying biology of lung cancer and also allow the development of new early detection tests and the identification of changes in the cancer protein network that are associated with prognosis and drug resistance.     

Early diagnostic protein biomarkers for breast cancer: how far have we come?

Many studies have used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to search for blood-based proteins that are related to the presence of breast cancer. We review the biomarkers discovered or targeted measured by these methods and discuss the strengths and weaknesses of these studies. We highlight two proteins that were most often related to breast cancer: C3a des-arginine anaphylatoxin (C3adesArg) (molecular weight: 8,938 Da) and fragments of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4). In addition, we elaborate on three important methodological aspects related to these studies: protein identification, specificity of the markers, and disease heterogeneity. Finally, we propose some points to be addressed in future studies. These include the use of other analytical measurement techniques, need of protein identification, the importance of identical sample handling protocols for cases and controls, and the stratification of the results according to molecular subtypes and stages of breast cancer. Ultimately this may lead to the discovery of new and valid breast cancer specific biomarkers.     

Peptide differential display of serum-free conditioned medium from cancer cell lines.

Conditioned medium (CM) from cultured cells is a source for screening small peptides of therapeutic or diagnostic value in cancer research. Mass spectrometry has recently enabled the profiling of peptides present in biological samples. We report a single-step extraction method to increase a chance to discover small peptides with a starting volume of 750 microl of serum-free CM. In combination with protein chip mass spectrometry, our protocol will contribute to the discovery of target peptides.