~（18）O标记定量蛋白质组结合LCM技术筛查胃癌标志物
|
摘要
研究背景:胃癌是目前世界上发病率第四位的肿瘤,居消化道恶性肿瘤发病率及病死率的第一位。其发病有着明显的地域分布特点,2/3的病例分布在发展中国家,尤以日本、中国及其它东亚国家高发。虽然研究结果认为胃癌的发病与幽门螺杆菌(helicobacter pylori,Hp)感染、遗传因素和环境因素密切相关,但胃癌的发病机制目前仍然不清楚。由于缺乏胃癌早期诊断、监测疾病过程的特异肿瘤标志物,大多数胃癌患者确诊时已经处于中晚期。早期胃癌根治术5年生存率可达90%～95%,而中晚期胃癌后5年生存率明显降低,仅为20%～30%。因此发现新的胃癌分子标志物将有助于胃癌的诊断、治疗和发病机制研究。
近年来,蛋白质组学技术已经成为研究临床肿瘤疾病普查和早期诊断蛋白质标记物的有效工具,同时为研究肿瘤发生和发展的机制提供了技术平台。常用的蛋白质组分析技术(双向聚丙烯酰胺凝胶电泳,two dimensional gel electrophoresis,2DE)存在敏感性、特异性、重复性较差,对疏水蛋白、小分子蛋白、膜蛋白分离有限等缺陷。因此采用高通量、更加精确的定量蛋白质组方法显得非常必要。基于稳定同位素标记与质谱联用的定量蛋白质组学是目前蛋白质组学研究技术中发展较快的领域,其中~(18)O稳定同位素标记技术因其技术相对简单,处理步骤少,试剂便宜等优点,在定量蛋白质组学研究中受到越来越多的关注。
肿瘤组织与其起源的正常组织比较蛋白质组学研究是发现肿瘤标志物和治疗靶标的最直接和合理的方式之一。然而,采用组织样本进行蛋白质组学研究的主要障碍是组织的异质性。因此,为提高比较蛋白质组学研究筛选肿瘤分子标志物的准确性,有必要纯化靶细胞用于蛋白质组学研究。最近发展起来的激光捕获显微切割(LCM)技术,以其简单、快速、精确度高等多功能特点,成功地解决了从所需标本不同成分中获取纯净细胞这一问题,广泛用于肿瘤学、细胞发生学和其他学科的研究,为肿瘤蛋白质组学研究提供了最佳的生物样本。
为了分离鉴定胃癌相关蛋白,筛查胃癌分子靶标,本研究采用LCM技术分别从手术胃腺癌组织和良性胃黏膜上皮组织(non-malignant gastric epithelial tissue,NMGET)样本中纯化相应的胃腺癌细胞(gastric adenocarcinoma cell,GAC)及其正常胃黏膜上皮细胞(Normal gastric epithelial cell,NGEC)。~(18)O稳定同位素标记定量蛋白质组学方法分离鉴定两种细胞间的差异蛋白质。验证并探讨差异蛋白质的临床病理意义。
第一章~(18)O标记定量蛋白质组学结合LCM技术筛选胃腺癌差异表达蛋白质
目的:准确筛查GAC和NGEC差异表达蛋白质。方法:LCM技术纯化GAC和NGEC;应用1D-SDS-PAGE技术预分离两种样本总蛋白;优化稳定高效的~(18)O/~(16)O标记技术,并用~(18)O/~(16)O分别标记GAC和NGEC多肽混合物,纳升级反相液相色谱串联质谱(Nano-RPLC-MS/MS)分离鉴定差异蛋白质。结果:建立了稳定高效的~(18)O标记技术;总共分离鉴定出306个蛋白质,78个蛋白质差异表达在2倍以上,其中42个蛋白在GAC中高表达,36个蛋白较NGEC中表达降低。结论:~(18)O标记定量蛋白质组学结合LCM技术能够准确定量并鉴定胃腺癌差异蛋白质。该技术为实体瘤分子靶标的筛查提供了新的技术平台。
第二章胃癌差异蛋白质表达验证及临床病理意义研究
目的:验证胃癌差异蛋白质并探讨其临床病理意义。方法:Western blotting检测了5个差异表达蛋白质(Moesin、Periostin、AnnexinA2、AnnexinA4和RKIP)在GAC和NGEC中的表达水平;免疫组化(IHC)检测RKIP、S100A9、AnnexinA2和AnnexinA4等蛋白在70例良性胃黏膜组织、118例胃癌组织和35例转移的淋巴结组织中的表达。结果:(1)Western blotting结果显示,Moesin、Periostin、AnnexinA2、AnnexinA4在GAC中高表达,RKIP在GAC中低表达。(2)免疫组化(IHC)结果显示,RKIP蛋白在良性胃黏膜组织中、胃癌组织和转移的淋巴结组织中阳性表达率分别为97.14%(68/70)、45.76%(54/118)、0(0/35)。RKIP蛋白表达与胃癌的浸润深度、TNM分期及淋巴结转移成负相关,与分化程度成正相关(P＜0.01)。(3)S100A9在良性胃黏膜组织、胃癌组织和转移的淋巴结组织中阳性表达率分别为高表达32.86%(23/70)、61.02%(72/118)、82.86%(29/35);S100A9蛋白表达与胃癌的TNM分期及淋巴结转移成正相关,与分化程度成正相关(P＜0.05);且在弥漫性胃癌中较肠型胃癌中表达更显著(P＜0.05)。(4)AnnexinA2在良性胃黏膜组织和胃癌组织阳性表达率分别为42.86%(30/70)、59.32%(70/118);其表达与胃癌的浸润深度、TNM分期及淋巴结转移成正相关(P＜0.05)。(5)AnnexinA4在良性胃黏膜组织和胃癌组织阳性表达率分别为38.57%(27/70)、55.93%(66/118)。其表达与胃癌的浸润深度、TNM分期及淋巴结转移成正相关(P＜0.05)。结论:Western blotting和IHC验证差异蛋白表达水平与~(18)O标记定量蛋白质组结果一致,~(18)O标记定量蛋白质组技术定量结果准确可靠。RKIP、S100A9、AnnexinA2和AnnexinA4蛋白与胃癌的恶性生物学行为相关,有望成为潜在的诊断胃癌、预测胃癌转移、鉴别胃癌分化程度、浸润深度及TNM分期的分子标志物。
Background: Gastric cancer (GC) is the fourth most common cancer and the second leading cause of cancer-related death behind lung cancer in the world. There are marked geographic variations in gastric cancer incidence, with the highest rates in China, Korea, Japan and South America. As an etiologically multi-factorial disease, carcinogenesis of gastric cancer may result from combined effects of helicobacter pylori, genetic and environmental factors. Although numerous efforts have been made to reveal the molecular mechanism of GC carcinogenesis, it remains poorly understood. And due to lack of suitable and specific biomarkers for early detection and monitoring of disease progress, most patients are diagnosed at an advanced stage. If being diagnosed in early stage, after operation, patients' five-year survival rates can reach 90% to 95%. But in advanced stage, the five-year survival rates are only 20-30%, mostly because of local recurrence and distant metastasis. In this regard, the identification of specific biomarkers is therefore desperately needed for gastric cancer.
Proteomics has been introduced to the field of cancer research as an effective approach at identifying differentially expressed proteins associated with cancer development and progression. The high throughput proteomics approaches may uncover new biomarkers and therapeutic targets for cancer as well as reveal possible molecular mechanism underlying the disease. Because of the traditional two-dimensional gel electrophoresis (2DE) has a number of limitations, which include difficulties in analyzing membrane proteins and difficulties in analyzing proteins that have extreme isoelectric points and sizes, the reproducibility and sensitivity are lower. So it is necessary for developing higher throughout and more accurate proteomic technologies. Quantitative proteomics which are based on stable isotope labeling and mass spectrum are developing quickly. Compared with other isotopic labeling strategies, ~(18)O labeling method has several advantages including simple labeling procedures, cheap reagents.
Using clinical tissue samples from patients may be the most direct and persuasive way to find biomarkers and therapeutic targets for cancers by a proteomic approach. A major obstacle, however, to the analysis of tumor specimens is tissue heterogeneity. For identifying biomarkers more accurately by proteomic analysis, it is important to obtain homogeneous cell populations from a heterogeneous tissue. Laser capture microdissection (LCM) is a technique developed recently, by which specific cells may be separated from tissue slides, even from different stages and sites in a same sample. It is a very important technique in molecular pathology and tumor genomics study for its success in solving the question of cellular heterogeneity.
To search for gastric adenocarcinoma biomarkers, we try to use LCM to purify the target cells from gastric adenocarcinoma (GA) and non-malignant gastric epithelial tissues (NMGET). ~(18)O labeling quantitative proteomics would be preformed to identify the differentially expressed proteins between gastric adenocarcinoma cells (GAC) and normal gastric epithelial cells (NGEC). Furthermore, clincopathological significances of the differential proteins would be studied.
Chapter 1 Identification of differentially expressed proteins by ~(18)O stable isotope labeling quantitative proteomics and LCM
Objective: To separate and identify differentially expressed proteins of GA. Methods: Firstly, we performed LCM to purify both GAC and NGEC from paired surgical specimens of human GA. Then, the proteins extracted from these cells were prefractionated by one-dimensional SDS-polyacrylamide gel electrophoresis (1D-SDS-PAGE). The fractionated proteins were trypsined and then labeled with ~(18)O-water and ~(16)O-water respectively. The two group labeled peptides were then mixed and analyzed by Nano-RPLC-MS/MS. Results: A total of 306 proteins were identified and quantified. Among these proteins, 78 proteins were differentially expressed between GAC and NGEC (42 proteins are up-regulated in GAC and 36 proteins are down-regulated). Conclusions:The procedure of ~(18)O stable isotope labeling quantitative proteomics coupled with LCM could identify and quantify the differential proteins of GA accurately, which provides a new choice for investigating biomarkers of solid tumor.
Chapter 2 Validation of differential proteins and study the clincopathological significances
Objective: To validate differential proteins and study the clincopathological significances of these differential proteins. Methods: Western blotting was used to detect the expression levels of five differential proteins (Moesin, Periostin, AnnexinA2, AnnexinA4 and RKIP) in GAC and NGEC. Immunohistochemistry (IHC) were performed to detected the expression of RKIP, S100A9, AnnexinA2 and AnnexinA4 in 70 cases of NMGET, 118 cases of GA, and matched positive lymph node (LN) specimens of primary GC. Results: (1) The results of western blotting showed that the express levels of five proteins. Moesin, Periostin, AnnexinA2, AnnexinA4 were higher in GAC than NGEC. RKIP was downexpressed in GAC versus NGEC. (2) The results of IHC showed, in the groups of NMGET, GA, and matched LN tissue, the positive expressed rates of RKIP were 97.14% (68/70)、45.76% (54/118)、0 (0/35), respectively; and positive expression of RKIP protein was closely correlated with deeper invasion, poor histological differentiation, TNM stage and lymphoid node metastasis in gastric cancer (P< 0.01). (3) in the groups of NMGET, GA, and matched LN tissue, the positive expressed rates of S100A9 were 32.86% (23/70)、61.02% (72/118)、82.86% (29/35), respectively; and expression of S100A9 has a positive correlation with TNM stage and lymphoid node metastasis in gastric cancer, but a negative correlation with histological differentiation (P< 0.05); and the expression of S100A9 was higher in intestinal type caner than diffuse type. (4) In the groups of NMGET and GA, the positive expressed rates of AnnexinA2 were 42.86% (30/70), 59.32% (70/118), respectively; and positive expression of AnnexinA2 were closely correlated with deeper invasion, poor histological differentiation, TNM stage and lymphoid node metastasis in gastric cancer (P< 0.05). (5) In the groups of NMGET and GA, the positive expressed rates of AnnenxinA4 were 38.57% (27/70), 55.93% (66/118), respectively; and positive expression of AnnexinA4 were closely correlated with deeper invasion, poor histological differentiation, TNM stage and lymphoid node metastasis in gastric cancer (P< 0.05). Conclusions: These results of western blotting and IHC were well consistent with the ~(18)O quantitative proteomics data, which suggested that ~(18)O quantitative proteomics are accurate and reliable. RKIP, S100A9, AnenxinA2 and AnnexinA4 proteins might affect the biological behavior of GC and be potential biomarkers for differentiation, invasion and metastasis of GC.
近年来,蛋白质组学技术已经成为研究临床肿瘤疾病普查和早期诊断蛋白质标记物的有效工具,同时为研究肿瘤发生和发展的机制提供了技术平台。常用的蛋白质组分析技术(双向聚丙烯酰胺凝胶电泳,two dimensional gel electrophoresis,2DE)存在敏感性、特异性、重复性较差,对疏水蛋白、小分子蛋白、膜蛋白分离有限等缺陷。因此采用高通量、更加精确的定量蛋白质组方法显得非常必要。基于稳定同位素标记与质谱联用的定量蛋白质组学是目前蛋白质组学研究技术中发展较快的领域,其中~(18)O稳定同位素标记技术因其技术相对简单,处理步骤少,试剂便宜等优点,在定量蛋白质组学研究中受到越来越多的关注。
肿瘤组织与其起源的正常组织比较蛋白质组学研究是发现肿瘤标志物和治疗靶标的最直接和合理的方式之一。然而,采用组织样本进行蛋白质组学研究的主要障碍是组织的异质性。因此,为提高比较蛋白质组学研究筛选肿瘤分子标志物的准确性,有必要纯化靶细胞用于蛋白质组学研究。最近发展起来的激光捕获显微切割(LCM)技术,以其简单、快速、精确度高等多功能特点,成功地解决了从所需标本不同成分中获取纯净细胞这一问题,广泛用于肿瘤学、细胞发生学和其他学科的研究,为肿瘤蛋白质组学研究提供了最佳的生物样本。
为了分离鉴定胃癌相关蛋白,筛查胃癌分子靶标,本研究采用LCM技术分别从手术胃腺癌组织和良性胃黏膜上皮组织(non-malignant gastric epithelial tissue,NMGET)样本中纯化相应的胃腺癌细胞(gastric adenocarcinoma cell,GAC)及其正常胃黏膜上皮细胞(Normal gastric epithelial cell,NGEC)。~(18)O稳定同位素标记定量蛋白质组学方法分离鉴定两种细胞间的差异蛋白质。验证并探讨差异蛋白质的临床病理意义。
第一章~(18)O标记定量蛋白质组学结合LCM技术筛选胃腺癌差异表达蛋白质
目的:准确筛查GAC和NGEC差异表达蛋白质。方法:LCM技术纯化GAC和NGEC;应用1D-SDS-PAGE技术预分离两种样本总蛋白;优化稳定高效的~(18)O/~(16)O标记技术,并用~(18)O/~(16)O分别标记GAC和NGEC多肽混合物,纳升级反相液相色谱串联质谱(Nano-RPLC-MS/MS)分离鉴定差异蛋白质。结果:建立了稳定高效的~(18)O标记技术;总共分离鉴定出306个蛋白质,78个蛋白质差异表达在2倍以上,其中42个蛋白在GAC中高表达,36个蛋白较NGEC中表达降低。结论:~(18)O标记定量蛋白质组学结合LCM技术能够准确定量并鉴定胃腺癌差异蛋白质。该技术为实体瘤分子靶标的筛查提供了新的技术平台。
第二章胃癌差异蛋白质表达验证及临床病理意义研究
目的:验证胃癌差异蛋白质并探讨其临床病理意义。方法:Western blotting检测了5个差异表达蛋白质(Moesin、Periostin、AnnexinA2、AnnexinA4和RKIP)在GAC和NGEC中的表达水平;免疫组化(IHC)检测RKIP、S100A9、AnnexinA2和AnnexinA4等蛋白在70例良性胃黏膜组织、118例胃癌组织和35例转移的淋巴结组织中的表达。结果:(1)Western blotting结果显示,Moesin、Periostin、AnnexinA2、AnnexinA4在GAC中高表达,RKIP在GAC中低表达。(2)免疫组化(IHC)结果显示,RKIP蛋白在良性胃黏膜组织中、胃癌组织和转移的淋巴结组织中阳性表达率分别为97.14%(68/70)、45.76%(54/118)、0(0/35)。RKIP蛋白表达与胃癌的浸润深度、TNM分期及淋巴结转移成负相关,与分化程度成正相关(P＜0.01)。(3)S100A9在良性胃黏膜组织、胃癌组织和转移的淋巴结组织中阳性表达率分别为高表达32.86%(23/70)、61.02%(72/118)、82.86%(29/35);S100A9蛋白表达与胃癌的TNM分期及淋巴结转移成正相关,与分化程度成正相关(P＜0.05);且在弥漫性胃癌中较肠型胃癌中表达更显著(P＜0.05)。(4)AnnexinA2在良性胃黏膜组织和胃癌组织阳性表达率分别为42.86%(30/70)、59.32%(70/118);其表达与胃癌的浸润深度、TNM分期及淋巴结转移成正相关(P＜0.05)。(5)AnnexinA4在良性胃黏膜组织和胃癌组织阳性表达率分别为38.57%(27/70)、55.93%(66/118)。其表达与胃癌的浸润深度、TNM分期及淋巴结转移成正相关(P＜0.05)。结论:Western blotting和IHC验证差异蛋白表达水平与~(18)O标记定量蛋白质组结果一致,~(18)O标记定量蛋白质组技术定量结果准确可靠。RKIP、S100A9、AnnexinA2和AnnexinA4蛋白与胃癌的恶性生物学行为相关,有望成为潜在的诊断胃癌、预测胃癌转移、鉴别胃癌分化程度、浸润深度及TNM分期的分子标志物。
Background: Gastric cancer (GC) is the fourth most common cancer and the second leading cause of cancer-related death behind lung cancer in the world. There are marked geographic variations in gastric cancer incidence, with the highest rates in China, Korea, Japan and South America. As an etiologically multi-factorial disease, carcinogenesis of gastric cancer may result from combined effects of helicobacter pylori, genetic and environmental factors. Although numerous efforts have been made to reveal the molecular mechanism of GC carcinogenesis, it remains poorly understood. And due to lack of suitable and specific biomarkers for early detection and monitoring of disease progress, most patients are diagnosed at an advanced stage. If being diagnosed in early stage, after operation, patients' five-year survival rates can reach 90% to 95%. But in advanced stage, the five-year survival rates are only 20-30%, mostly because of local recurrence and distant metastasis. In this regard, the identification of specific biomarkers is therefore desperately needed for gastric cancer.
Proteomics has been introduced to the field of cancer research as an effective approach at identifying differentially expressed proteins associated with cancer development and progression. The high throughput proteomics approaches may uncover new biomarkers and therapeutic targets for cancer as well as reveal possible molecular mechanism underlying the disease. Because of the traditional two-dimensional gel electrophoresis (2DE) has a number of limitations, which include difficulties in analyzing membrane proteins and difficulties in analyzing proteins that have extreme isoelectric points and sizes, the reproducibility and sensitivity are lower. So it is necessary for developing higher throughout and more accurate proteomic technologies. Quantitative proteomics which are based on stable isotope labeling and mass spectrum are developing quickly. Compared with other isotopic labeling strategies, ~(18)O labeling method has several advantages including simple labeling procedures, cheap reagents.
Using clinical tissue samples from patients may be the most direct and persuasive way to find biomarkers and therapeutic targets for cancers by a proteomic approach. A major obstacle, however, to the analysis of tumor specimens is tissue heterogeneity. For identifying biomarkers more accurately by proteomic analysis, it is important to obtain homogeneous cell populations from a heterogeneous tissue. Laser capture microdissection (LCM) is a technique developed recently, by which specific cells may be separated from tissue slides, even from different stages and sites in a same sample. It is a very important technique in molecular pathology and tumor genomics study for its success in solving the question of cellular heterogeneity.
To search for gastric adenocarcinoma biomarkers, we try to use LCM to purify the target cells from gastric adenocarcinoma (GA) and non-malignant gastric epithelial tissues (NMGET). ~(18)O labeling quantitative proteomics would be preformed to identify the differentially expressed proteins between gastric adenocarcinoma cells (GAC) and normal gastric epithelial cells (NGEC). Furthermore, clincopathological significances of the differential proteins would be studied.
Chapter 1 Identification of differentially expressed proteins by ~(18)O stable isotope labeling quantitative proteomics and LCM
Objective: To separate and identify differentially expressed proteins of GA. Methods: Firstly, we performed LCM to purify both GAC and NGEC from paired surgical specimens of human GA. Then, the proteins extracted from these cells were prefractionated by one-dimensional SDS-polyacrylamide gel electrophoresis (1D-SDS-PAGE). The fractionated proteins were trypsined and then labeled with ~(18)O-water and ~(16)O-water respectively. The two group labeled peptides were then mixed and analyzed by Nano-RPLC-MS/MS. Results: A total of 306 proteins were identified and quantified. Among these proteins, 78 proteins were differentially expressed between GAC and NGEC (42 proteins are up-regulated in GAC and 36 proteins are down-regulated). Conclusions:The procedure of ~(18)O stable isotope labeling quantitative proteomics coupled with LCM could identify and quantify the differential proteins of GA accurately, which provides a new choice for investigating biomarkers of solid tumor.
Chapter 2 Validation of differential proteins and study the clincopathological significances
Objective: To validate differential proteins and study the clincopathological significances of these differential proteins. Methods: Western blotting was used to detect the expression levels of five differential proteins (Moesin, Periostin, AnnexinA2, AnnexinA4 and RKIP) in GAC and NGEC. Immunohistochemistry (IHC) were performed to detected the expression of RKIP, S100A9, AnnexinA2 and AnnexinA4 in 70 cases of NMGET, 118 cases of GA, and matched positive lymph node (LN) specimens of primary GC. Results: (1) The results of western blotting showed that the express levels of five proteins. Moesin, Periostin, AnnexinA2, AnnexinA4 were higher in GAC than NGEC. RKIP was downexpressed in GAC versus NGEC. (2) The results of IHC showed, in the groups of NMGET, GA, and matched LN tissue, the positive expressed rates of RKIP were 97.14% (68/70)、45.76% (54/118)、0 (0/35), respectively; and positive expression of RKIP protein was closely correlated with deeper invasion, poor histological differentiation, TNM stage and lymphoid node metastasis in gastric cancer (P< 0.01). (3) in the groups of NMGET, GA, and matched LN tissue, the positive expressed rates of S100A9 were 32.86% (23/70)、61.02% (72/118)、82.86% (29/35), respectively; and expression of S100A9 has a positive correlation with TNM stage and lymphoid node metastasis in gastric cancer, but a negative correlation with histological differentiation (P< 0.05); and the expression of S100A9 was higher in intestinal type caner than diffuse type. (4) In the groups of NMGET and GA, the positive expressed rates of AnnexinA2 were 42.86% (30/70), 59.32% (70/118), respectively; and positive expression of AnnexinA2 were closely correlated with deeper invasion, poor histological differentiation, TNM stage and lymphoid node metastasis in gastric cancer (P< 0.05). (5) In the groups of NMGET and GA, the positive expressed rates of AnnenxinA4 were 38.57% (27/70), 55.93% (66/118), respectively; and positive expression of AnnexinA4 were closely correlated with deeper invasion, poor histological differentiation, TNM stage and lymphoid node metastasis in gastric cancer (P< 0.05). Conclusions: These results of western blotting and IHC were well consistent with the ~(18)O quantitative proteomics data, which suggested that ~(18)O quantitative proteomics are accurate and reliable. RKIP, S100A9, AnenxinA2 and AnnexinA4 proteins might affect the biological behavior of GC and be potential biomarkers for differentiation, invasion and metastasis of GC.
引文
[1]贺福初.蛋白质组(proteome)研究--后基因组时代的生力军[J].科学通报,1999(02):113-122.
[2]Aebersold R,Mann M.Mass spectrometry-based proteomics.[J].Nature,2003,422(6928):198-207.
[3]Washburn M P,Wolters D,Jr Yates R.Large-scale analysis of the yeast proteome by multidimensional protein identification technology.[J].Nat Biotechnol,2001,19(3):242-247.
[4]Huber L A.Is proteomics heading in the wrong direction?[J].Nat Rev Mol Cell Biol,2003,4(1):74-80.
[5]Lee K H.Proteomics:a technology-driven and technology-limited discovery science.[J].Trends Biotechnol,2001,19(6):217-222.
[6]Wasinger V C,Cordwell S J,Cerpa-Poljak A,et al.Progress with gene-product mapping of the Mollicutes:Mycoplasma genitalium.[J].Electrophoresis,1995,16(7):1090-1094.
[7]Anderson N L,Anderson N G.Proteome and proteomics:new technologies,new concepts,and new words.[J].Electrophoresis,1998,19(11):1853-1861.
[8]Patterson S D,Aebersold R H.Proteomics:the first decade and beyond.[J].Nat Genet,2003,33 Suppl:311-323.
[9]Aggarwal K,Lee K H.Functional genomics and proteomics as a foundation for systems biology.[J].Brief Funct Genomic Proteomic,2003,2(3):175-184.
[10]Schmid M B.Structural proteomics:the potential of high-throughput structure determination.[J].Trends Microbiol,2002,10(10 Suppl):27-31.
[11]Kolch W,Mischak H,Pitt A R.The molecular make-up of a tumour:proteomics in cancer research.[J].Clin Sci(Lond),2005,108(5):369-383.
[12]刘慧玲,张养军,钱小红.稳定同位素化学标记结合质谱技术在定量蛋白质组学中的应用[J].生物技术通讯,2006(03):460-464.
[13]Unlu M,Morgan M E,Minden J S.Difference gel electrophoresis:a single gel method for detecting changes in protein extracts.[J].Electrophoresis,1997,18(11):2071-2077.
[14]Sechi S,Oda Y.Quantitative proteomics using mass spectrometry.[J].Curr Opin Chem Biol,2003,7(1):70-77.
[15] Ghosh A. Computational bioinorganic chemistry. Part III. The tools of the trade: from high-level ab initio calculations to structural bioinformatics.[J]. Curr Opin Chem Biol,2003,7(1):110-112.
[16] Mann M. Quantitative proteomics?[J]. Nat Biotechnol,1999,17(10):954-955. [17] Beynon R J, Pratt J M. Metabolic labeling of proteins for proteomics.[J]. Mol Cell Proteomics,2005,4(7):857-872.
[18] Oda Y, Huang K, Cross F R, et al. Accurate quantitation of protein expression and site-specific phosphorylation.[J]. Proc Natl Acad Sci U S A,1999,96(12):6591-6596.
[19] Ong S E, Blagoev B, Kratchmarova I, et al. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.[J]. Mol Cell Proteomics,2002,1(5):376-386.
[20] Gygi S P, Rist B, Gerber S A, et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.[J]. Nat Biotechnol, 1999,17(10):994-999.
[21] Rao K C, Carruth R T, Miyagi M. Proteolytic 180 labeling by peptidyl-Lys metalloendopeptidase for comparative proteomics.[J]. J Proteome Res,2005,4(2):507-514.
[22] Wang Y K, Ma Z, Quinn D F, et al. Inverse 180 labeling mass spectrometry for the rapid identification of marker/target proteins.[J]. Anal Chem,2001,73(15):3742-3750.
[23] Bantscheff M, Dumpelfeld B, Kuster B. Femtomol sensitivity post-digest (18)O labeling for relative quantification of differential protein complex composition.[J]. Rapid Commun Mass Spectrom,2004,18(8):869-876.
[24] Sakai J, Kojima S, Yanagi K, et al. 180-labeling quantitative proteomics using an ion trap mass spectrometer.[J]. Proteomics,2005,5(1):16-23.
[25] Hicks W A, Halligan B D, Slyper R Y, et al. Simultaneous quantification and identification using 18O labeling with an ion trap mass spectrometer and the analysis software application "ZoomQuant".[J]. J Am Soc Mass Spectrom,2005,16(6):916-925.
[26] Old W M, Meyer-Arendt K, Aveline-Wolf L, et al. Comparison of label-free methods for quantifying human proteins by shotgun proteomics.[J]. Mol Cell Proteomics,2005,4(10):1487-1502.
[27] Chen X, Cushman S W, Pannell L K, et al. Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach.[J].J Proteome Res,2005,4(2):570-577.
[28]Korbel S,Schumann M,Bittorf T,et al.Relative quantification of erythropoietin receptor-dependent phosphoproteins using in-gel 18O-labeling and tandem mass spectrometry.[J].Rapid Commun Mass Spectrom,2005,19(16):2259-2271.
[29]Kobayashi M,Iwamatsu A,Shinohara-Kanda A,et al.Activation of ErbB3-PI3-kinase pathway is correlated with malignant phenotypes of adenocarcinomas.[J].Oncogene,2003,22(9):1294-1301.
[30]Tomlinson A J,Hincapie M,Morris G E,et al.Global proteome analysis of a human gastric carcinoma.[J].Electrophoresis,2002,23(18):3233-3240.
[31]贾继辉,陈春燕,于修平,et al.SV40转化的人胃黏膜上皮细胞与胃癌细胞间的比较蛋白质组学研究[J].中华微生物学和免疫学杂志,2004(03):66-69.
[32]Kim H K,Park W S,Kang S H,et al.Mitochondrial alterations in human gastric carcinoma cell line.[J].Am J Physiol Cell Physiol,2007,293(2):761-771.
[33]Zhang Z,Jr Bast R C,Yu Y,et al.Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer.[J].Cancer Res,2004,64(16):5882-5890.
[34]Ornstein D K,Rayford W,Fusaro V A,et al.Serum proteomic profiling can discriminate prostate cancer from benign prostates in men with total prostate specific antigen levels between 2.5 and 15.0 ng/ml.[J].J Urol,2004,172(4 Pt 1):1302-1305.
[35]Steel L F,Shumpert D,Trotter M,et al.A strategy for the comparative analysis of serum proteomes for the discovery of biomarkers for hepatocellular carcinoma.[J].Proteomics,2003,3(5):601-609.
[36]Yan J X,Wait R,Berkelman T,et al.A modified silver staining protocol for visualization of proteins compatible with matrix-assisted laser desorption/ionization and electrospray ionization-mass spectrometry.[J].Electrophoresis,2000,21(17):3666-3672.
[37]Li C,Chen Z,Xiao Z,et al.Comparative proteomics analysis of human lung squamous carcinoma.[J].Biochem Biophys Res Commun,2003,309(1):253-260.
[38]Shimada S,Tashima S,Yamaguchi K,et al.Carcinogenesis of intestinal-type gastric cancer and colorectal cancer is commonly accompanied by expression of brain(fetal)-type glycogen phosphorylase.[J].J Exp Clin Cancer Res,1999,18(1):111-118.
[39]Yu J K,Chen Y D,Zheng S.An integrated approach to the detection of colorectal cancer utilizing proteomics and bioinformatics.[J].World J Gastroenterol,2004,10(21):3127-3131.
[40]Qian H G,Shen J,Ma H,et al.Preliminary study on proteomics of gastric carcinoma and its clinical significance.[J].World J Gastroenterol,2005,11(40):6249-6253.
[41]Su Y,Shen J,Qian H,et al.Diagnosis of gastric cancer using decision tree classification of mass spectral data.[J].Cancer Sci,2007,98(1):37-43.
[42]Poon T C,Sung J J,Chow S M,et al.Diagnosis of gastric cancer by serum proteomic fingerprinting.[J].Gastroenterology,2006,130(6):1858-1864.
[43]Liang Y,Fang M,Li J,et al.Serum proteomic patterns for gastric lesions as revealed by SELDI mass spectrometry.[J].Exp Mol Pathol,2006,81(2):176-180.
[44]Ren H,Du N,Liu G,et al.Analysis of variabilities of serum proteomic spectra in patients with gastric cancer before and after operation.[J].World J Gastroenterol,2006,12(17):2789-2792.
[45]刘池波.蛋白质组技术在胃癌相关标志物筛查中的应用[J].实用肿瘤学杂志,2008(03):204-207.
[46]高春芳,李冬晖,赵光,et al.胃癌患者血清比较蛋白质组学研究[J].解放军医学杂志,2005(06):457-459.
[47]Ebert M P,Lamer S,Meuer J,et al.Identification of the thrombin light chain a as the single best mass for differentiation of gastric cancer patients from individuals with dyspepsia by proteome analysis.[J].J Proteome Res,2005,4(2):586-590.
[48]Marshall S,Munoz G,Sierralta G,et al.Differential protein phosphorylation in human gastric adenocarcinomas.[J].Cell Mol Biol,1991,37(8):785-791.
[49]Chen J,Kahne T,Rocken C,et al.Proteome analysis of gastric cancer metastasis by two-dimensional gel electrophoresis and matrix assisted laser desorption/ionization-mass spectrometry for identification of metastasis-related proteins.[J].J Proteome Res,2004,3(5):1009-1016.
[50]Ha G H,Lee S U,Kang D G,et al.Proteome analysis of human stomach tissue:separation of soluble proteins by two-dimensional polyacrylamide gel electrophoresis and identification by mass spectrometry.[J].Electrophoresis,2002,23(15):2513-2524.
[51]He Q Y,Cheung Y H,Leung S Y,et al.Diverse proteomic alterations in gastric adenocarcinoma.[J].Proteomics,2004,4(10):3276-3287.
[52]Ryu J W,Kim H J,Lee Y S,et al.The proteomics approach to find biomarkers in gastric cancer.[J].J Korean Med Sci,2003,18(4):505-509.
[53]Wang K J,Wang R T,Zhang J Z.Identification of tumor markers using two-dimensional electrophoresis in gastric carcinoma.[J].World J Gastroenterol,2004,10(15):2179-2183.
[54]Ebert M P,Kruger S,Fogeron M L,et al.Overexpression of cathepsin B in gastric cancer identified by proteome analysis.[J].Proteomics,2005,5(6):1693-1704.
[55]Yoshihara T,Kadota Y,Yoshimura Y,et al.Proteomic alteration in gastic adenocarcinomas from Japanese patients.[J].Mol Cancer,2006,5:75.
[56]李艳兰,贺修胜,龙治峰,et al.高分化胃腺癌组织表达缺失蛋白质分析[J].南华大学学报(医学版),2005(01):4-8.
[57]Lee J R,Baxter T M,Yamaguchi H,et al.Differential protein analysis of spasomolytic polypeptide expressing metaplasia using laser capture microdissection and two-dimensional difference gel electrophoresis.[J].Appl Immunohistochem Mol Morphol,2003,11(2):188-193.
[58]Melle C,Ernst G,Schimmel B,et al.Characterization of pepsinogen C as a potential biomarker for gastric cancer using a histo-proteomic approach.[J].J Proteome Res,2005,4(5):1799-1804.
[59]Ernst G,Melle C,Schimmel B,et al.Proteohistography-direct analysis of tissue with high sensitivity and high spatial resolution using ProteinChip technology.[J].J Histochem Cytochem,2006,54(1):13-17.
[60]Lee K,Kye M,Jang J S,et al.Proteomic analysis revealed a strong association of a high level of alphal-antitrypsin in gastric juice with gastric cancer.[J].Proteomics,2004,4(11):3343-3352.
[61]Jungblut P R,Bumann D,Haas G,et al.Comparative proteome analysis of Helicobacter pylori.[J].Mol Microbiol,2000,36(3):710-725.
[62]Krah A,Schmidt F,Becher D,et al.Analysis of automatically generated peptide mass fingerprints of cellular proteins and antigens from Helicobacter pylori 26695 separated by two-dimensional electrophoresis.[J]. Mol Cell Proteomics,2003,2(12): 1271 -1283.
[63] Mckenzie A, Van Herk M, Mijnheer B. Margins for geometric uncertainty around organs at risk in radiotherapy.[J]. Radiother Oncol,2002,62(3):299-307.
[64] Enroth H, Akerlund T, Sillen A, et al. Clustering of clinical strains of Helicobacter pylori analyzed by two-dimensional gel electrophoresis.[J]. Clin Diagn Lab Immunol,2000,7(2):301-306.
[65] Li B Q, Zhang J Z, Zou Q H, et al. [Primary analysis on protein maps of Helicobacter pylori strains associated with gastric carcinoma][J]. Zhonghua Liu Xing Bing Xue Za Zhi,2003,24(6):439-442.
[66] Ha G H, Lee S U, Kang D G, et al. Proteome analysis of human stomach tissue: separation of soluble proteins by two-dimensional polyacrylamide gel electrophoresis and identification by mass spectrometry.[J]. Electrophoresis,2002,23(15):2513-2524.
[67] Krah A, Miehlke S, Pleissner K P, et al. Identification of candidate antigens for serologic detection of Helicobacter pylori-infected patients with gastric carcinoma.[J]. Int J Cancer,2004,108(3):456-463.
[68] Chuang M H, Wu M S, Lin J T, et al. Proteomic analysis of proteins expressed by Helicobacter pylori under oxidative stress.[J]. Proteomics,2005,5(15):3895-3901.
[69] Das S, Sierra J C, Soman K V, et al. Differential protein expression profiles of gastric epithelial cells following Helicobacter pylori infection using ProteinChips.[J]. J Proteome Res,2005,4(3):920-930.
[70] Sinha P, Hutter G, Kottgen E, et al. Increased expression of annexin I and thioredoxin detected by two-dimensional gel electrophoresis of drug resistant human stomach cancer cells.[J]. J Biochem Biophys Methods,1998,37(3):105-116.
[71] Sinha P, Poland J, Schnolzer M, et al. Characterization of the differential protein expression associated with thermoresistance in human gastric carcinoma cell lines.[J]. Electrophoresis,2001,22(14):2990-3000.
[72] Poland J, Schadendorf D, Lage H, et al. Study of therapy resistance in cancer cells with functional proteome analysis.[J]. Clin Chem Lab Med,2002,40(3):221-234.
[73] Yoo B C, Ku J L, Hong S H, et al. Decreased pyruvate kinase M2 activity linked to cisplatin resistance in human gastric carcinoma cell lines.[J]. Int J Cancer,2004,108(4):532-539.
[74] Ping S, Wang S, Zhang J, et al. Effect of all-trans-retinoic acid on mRNA binding protein p62 in human gastric cancer cells.[J]. Int J Biochem Cell Biol,2005,37(3):616-627.
[75] Zhang G, Wang G, Wang S, et al. Applying proteomic methodologies to analyze the effect of hexamethylene bisacetamide (HMBA) on proliferation and differentiation of human gastric carcinoma BGC-823 cells.[J]. Int J Biochem Cell Biol,2004,36(8):1613-1623.
[76] Shi P, Huang Z. Proteomic detection of changes in protein synthesis induced by lanthanum in BGC-823 human gastric cancer cells.[J]. Biometals,2005, 18(1):89-95.
[77] Banks R E, Dunn M J, Forbes M A, et al. The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis-preliminary findings.[J]. Electrophoresis,1999,20(4-5):689-700.
[78] Lehner B, Tischler J, Fraser A G. Systems biology: where it's at in 2005.[J]. Genome Biol,2005,6(8):338.
[2]Aebersold R,Mann M.Mass spectrometry-based proteomics.[J].Nature,2003,422(6928):198-207.
[3]Washburn M P,Wolters D,Jr Yates R.Large-scale analysis of the yeast proteome by multidimensional protein identification technology.[J].Nat Biotechnol,2001,19(3):242-247.
[4]Huber L A.Is proteomics heading in the wrong direction?[J].Nat Rev Mol Cell Biol,2003,4(1):74-80.
[5]Lee K H.Proteomics:a technology-driven and technology-limited discovery science.[J].Trends Biotechnol,2001,19(6):217-222.
[6]Wasinger V C,Cordwell S J,Cerpa-Poljak A,et al.Progress with gene-product mapping of the Mollicutes:Mycoplasma genitalium.[J].Electrophoresis,1995,16(7):1090-1094.
[7]Anderson N L,Anderson N G.Proteome and proteomics:new technologies,new concepts,and new words.[J].Electrophoresis,1998,19(11):1853-1861.
[8]Patterson S D,Aebersold R H.Proteomics:the first decade and beyond.[J].Nat Genet,2003,33 Suppl:311-323.
[9]Aggarwal K,Lee K H.Functional genomics and proteomics as a foundation for systems biology.[J].Brief Funct Genomic Proteomic,2003,2(3):175-184.
[10]Schmid M B.Structural proteomics:the potential of high-throughput structure determination.[J].Trends Microbiol,2002,10(10 Suppl):27-31.
[11]Kolch W,Mischak H,Pitt A R.The molecular make-up of a tumour:proteomics in cancer research.[J].Clin Sci(Lond),2005,108(5):369-383.
[12]刘慧玲,张养军,钱小红.稳定同位素化学标记结合质谱技术在定量蛋白质组学中的应用[J].生物技术通讯,2006(03):460-464.
[13]Unlu M,Morgan M E,Minden J S.Difference gel electrophoresis:a single gel method for detecting changes in protein extracts.[J].Electrophoresis,1997,18(11):2071-2077.
[14]Sechi S,Oda Y.Quantitative proteomics using mass spectrometry.[J].Curr Opin Chem Biol,2003,7(1):70-77.
[15] Ghosh A. Computational bioinorganic chemistry. Part III. The tools of the trade: from high-level ab initio calculations to structural bioinformatics.[J]. Curr Opin Chem Biol,2003,7(1):110-112.
[16] Mann M. Quantitative proteomics?[J]. Nat Biotechnol,1999,17(10):954-955. [17] Beynon R J, Pratt J M. Metabolic labeling of proteins for proteomics.[J]. Mol Cell Proteomics,2005,4(7):857-872.
[18] Oda Y, Huang K, Cross F R, et al. Accurate quantitation of protein expression and site-specific phosphorylation.[J]. Proc Natl Acad Sci U S A,1999,96(12):6591-6596.
[19] Ong S E, Blagoev B, Kratchmarova I, et al. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.[J]. Mol Cell Proteomics,2002,1(5):376-386.
[20] Gygi S P, Rist B, Gerber S A, et al. Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.[J]. Nat Biotechnol, 1999,17(10):994-999.
[21] Rao K C, Carruth R T, Miyagi M. Proteolytic 180 labeling by peptidyl-Lys metalloendopeptidase for comparative proteomics.[J]. J Proteome Res,2005,4(2):507-514.
[22] Wang Y K, Ma Z, Quinn D F, et al. Inverse 180 labeling mass spectrometry for the rapid identification of marker/target proteins.[J]. Anal Chem,2001,73(15):3742-3750.
[23] Bantscheff M, Dumpelfeld B, Kuster B. Femtomol sensitivity post-digest (18)O labeling for relative quantification of differential protein complex composition.[J]. Rapid Commun Mass Spectrom,2004,18(8):869-876.
[24] Sakai J, Kojima S, Yanagi K, et al. 180-labeling quantitative proteomics using an ion trap mass spectrometer.[J]. Proteomics,2005,5(1):16-23.
[25] Hicks W A, Halligan B D, Slyper R Y, et al. Simultaneous quantification and identification using 18O labeling with an ion trap mass spectrometer and the analysis software application "ZoomQuant".[J]. J Am Soc Mass Spectrom,2005,16(6):916-925.
[26] Old W M, Meyer-Arendt K, Aveline-Wolf L, et al. Comparison of label-free methods for quantifying human proteins by shotgun proteomics.[J]. Mol Cell Proteomics,2005,4(10):1487-1502.
[27] Chen X, Cushman S W, Pannell L K, et al. Quantitative proteomic analysis of the secretory proteins from rat adipose cells using a 2D liquid chromatography-MS/MS approach.[J].J Proteome Res,2005,4(2):570-577.
[28]Korbel S,Schumann M,Bittorf T,et al.Relative quantification of erythropoietin receptor-dependent phosphoproteins using in-gel 18O-labeling and tandem mass spectrometry.[J].Rapid Commun Mass Spectrom,2005,19(16):2259-2271.
[29]Kobayashi M,Iwamatsu A,Shinohara-Kanda A,et al.Activation of ErbB3-PI3-kinase pathway is correlated with malignant phenotypes of adenocarcinomas.[J].Oncogene,2003,22(9):1294-1301.
[30]Tomlinson A J,Hincapie M,Morris G E,et al.Global proteome analysis of a human gastric carcinoma.[J].Electrophoresis,2002,23(18):3233-3240.
[31]贾继辉,陈春燕,于修平,et al.SV40转化的人胃黏膜上皮细胞与胃癌细胞间的比较蛋白质组学研究[J].中华微生物学和免疫学杂志,2004(03):66-69.
[32]Kim H K,Park W S,Kang S H,et al.Mitochondrial alterations in human gastric carcinoma cell line.[J].Am J Physiol Cell Physiol,2007,293(2):761-771.
[33]Zhang Z,Jr Bast R C,Yu Y,et al.Three biomarkers identified from serum proteomic analysis for the detection of early stage ovarian cancer.[J].Cancer Res,2004,64(16):5882-5890.
[34]Ornstein D K,Rayford W,Fusaro V A,et al.Serum proteomic profiling can discriminate prostate cancer from benign prostates in men with total prostate specific antigen levels between 2.5 and 15.0 ng/ml.[J].J Urol,2004,172(4 Pt 1):1302-1305.
[35]Steel L F,Shumpert D,Trotter M,et al.A strategy for the comparative analysis of serum proteomes for the discovery of biomarkers for hepatocellular carcinoma.[J].Proteomics,2003,3(5):601-609.
[36]Yan J X,Wait R,Berkelman T,et al.A modified silver staining protocol for visualization of proteins compatible with matrix-assisted laser desorption/ionization and electrospray ionization-mass spectrometry.[J].Electrophoresis,2000,21(17):3666-3672.
[37]Li C,Chen Z,Xiao Z,et al.Comparative proteomics analysis of human lung squamous carcinoma.[J].Biochem Biophys Res Commun,2003,309(1):253-260.
[38]Shimada S,Tashima S,Yamaguchi K,et al.Carcinogenesis of intestinal-type gastric cancer and colorectal cancer is commonly accompanied by expression of brain(fetal)-type glycogen phosphorylase.[J].J Exp Clin Cancer Res,1999,18(1):111-118.
[39]Yu J K,Chen Y D,Zheng S.An integrated approach to the detection of colorectal cancer utilizing proteomics and bioinformatics.[J].World J Gastroenterol,2004,10(21):3127-3131.
[40]Qian H G,Shen J,Ma H,et al.Preliminary study on proteomics of gastric carcinoma and its clinical significance.[J].World J Gastroenterol,2005,11(40):6249-6253.
[41]Su Y,Shen J,Qian H,et al.Diagnosis of gastric cancer using decision tree classification of mass spectral data.[J].Cancer Sci,2007,98(1):37-43.
[42]Poon T C,Sung J J,Chow S M,et al.Diagnosis of gastric cancer by serum proteomic fingerprinting.[J].Gastroenterology,2006,130(6):1858-1864.
[43]Liang Y,Fang M,Li J,et al.Serum proteomic patterns for gastric lesions as revealed by SELDI mass spectrometry.[J].Exp Mol Pathol,2006,81(2):176-180.
[44]Ren H,Du N,Liu G,et al.Analysis of variabilities of serum proteomic spectra in patients with gastric cancer before and after operation.[J].World J Gastroenterol,2006,12(17):2789-2792.
[45]刘池波.蛋白质组技术在胃癌相关标志物筛查中的应用[J].实用肿瘤学杂志,2008(03):204-207.
[46]高春芳,李冬晖,赵光,et al.胃癌患者血清比较蛋白质组学研究[J].解放军医学杂志,2005(06):457-459.
[47]Ebert M P,Lamer S,Meuer J,et al.Identification of the thrombin light chain a as the single best mass for differentiation of gastric cancer patients from individuals with dyspepsia by proteome analysis.[J].J Proteome Res,2005,4(2):586-590.
[48]Marshall S,Munoz G,Sierralta G,et al.Differential protein phosphorylation in human gastric adenocarcinomas.[J].Cell Mol Biol,1991,37(8):785-791.
[49]Chen J,Kahne T,Rocken C,et al.Proteome analysis of gastric cancer metastasis by two-dimensional gel electrophoresis and matrix assisted laser desorption/ionization-mass spectrometry for identification of metastasis-related proteins.[J].J Proteome Res,2004,3(5):1009-1016.
[50]Ha G H,Lee S U,Kang D G,et al.Proteome analysis of human stomach tissue:separation of soluble proteins by two-dimensional polyacrylamide gel electrophoresis and identification by mass spectrometry.[J].Electrophoresis,2002,23(15):2513-2524.
[51]He Q Y,Cheung Y H,Leung S Y,et al.Diverse proteomic alterations in gastric adenocarcinoma.[J].Proteomics,2004,4(10):3276-3287.
[52]Ryu J W,Kim H J,Lee Y S,et al.The proteomics approach to find biomarkers in gastric cancer.[J].J Korean Med Sci,2003,18(4):505-509.
[53]Wang K J,Wang R T,Zhang J Z.Identification of tumor markers using two-dimensional electrophoresis in gastric carcinoma.[J].World J Gastroenterol,2004,10(15):2179-2183.
[54]Ebert M P,Kruger S,Fogeron M L,et al.Overexpression of cathepsin B in gastric cancer identified by proteome analysis.[J].Proteomics,2005,5(6):1693-1704.
[55]Yoshihara T,Kadota Y,Yoshimura Y,et al.Proteomic alteration in gastic adenocarcinomas from Japanese patients.[J].Mol Cancer,2006,5:75.
[56]李艳兰,贺修胜,龙治峰,et al.高分化胃腺癌组织表达缺失蛋白质分析[J].南华大学学报(医学版),2005(01):4-8.
[57]Lee J R,Baxter T M,Yamaguchi H,et al.Differential protein analysis of spasomolytic polypeptide expressing metaplasia using laser capture microdissection and two-dimensional difference gel electrophoresis.[J].Appl Immunohistochem Mol Morphol,2003,11(2):188-193.
[58]Melle C,Ernst G,Schimmel B,et al.Characterization of pepsinogen C as a potential biomarker for gastric cancer using a histo-proteomic approach.[J].J Proteome Res,2005,4(5):1799-1804.
[59]Ernst G,Melle C,Schimmel B,et al.Proteohistography-direct analysis of tissue with high sensitivity and high spatial resolution using ProteinChip technology.[J].J Histochem Cytochem,2006,54(1):13-17.
[60]Lee K,Kye M,Jang J S,et al.Proteomic analysis revealed a strong association of a high level of alphal-antitrypsin in gastric juice with gastric cancer.[J].Proteomics,2004,4(11):3343-3352.
[61]Jungblut P R,Bumann D,Haas G,et al.Comparative proteome analysis of Helicobacter pylori.[J].Mol Microbiol,2000,36(3):710-725.
[62]Krah A,Schmidt F,Becher D,et al.Analysis of automatically generated peptide mass fingerprints of cellular proteins and antigens from Helicobacter pylori 26695 separated by two-dimensional electrophoresis.[J]. Mol Cell Proteomics,2003,2(12): 1271 -1283.
[63] Mckenzie A, Van Herk M, Mijnheer B. Margins for geometric uncertainty around organs at risk in radiotherapy.[J]. Radiother Oncol,2002,62(3):299-307.
[64] Enroth H, Akerlund T, Sillen A, et al. Clustering of clinical strains of Helicobacter pylori analyzed by two-dimensional gel electrophoresis.[J]. Clin Diagn Lab Immunol,2000,7(2):301-306.
[65] Li B Q, Zhang J Z, Zou Q H, et al. [Primary analysis on protein maps of Helicobacter pylori strains associated with gastric carcinoma][J]. Zhonghua Liu Xing Bing Xue Za Zhi,2003,24(6):439-442.
[66] Ha G H, Lee S U, Kang D G, et al. Proteome analysis of human stomach tissue: separation of soluble proteins by two-dimensional polyacrylamide gel electrophoresis and identification by mass spectrometry.[J]. Electrophoresis,2002,23(15):2513-2524.
[67] Krah A, Miehlke S, Pleissner K P, et al. Identification of candidate antigens for serologic detection of Helicobacter pylori-infected patients with gastric carcinoma.[J]. Int J Cancer,2004,108(3):456-463.
[68] Chuang M H, Wu M S, Lin J T, et al. Proteomic analysis of proteins expressed by Helicobacter pylori under oxidative stress.[J]. Proteomics,2005,5(15):3895-3901.
[69] Das S, Sierra J C, Soman K V, et al. Differential protein expression profiles of gastric epithelial cells following Helicobacter pylori infection using ProteinChips.[J]. J Proteome Res,2005,4(3):920-930.
[70] Sinha P, Hutter G, Kottgen E, et al. Increased expression of annexin I and thioredoxin detected by two-dimensional gel electrophoresis of drug resistant human stomach cancer cells.[J]. J Biochem Biophys Methods,1998,37(3):105-116.
[71] Sinha P, Poland J, Schnolzer M, et al. Characterization of the differential protein expression associated with thermoresistance in human gastric carcinoma cell lines.[J]. Electrophoresis,2001,22(14):2990-3000.
[72] Poland J, Schadendorf D, Lage H, et al. Study of therapy resistance in cancer cells with functional proteome analysis.[J]. Clin Chem Lab Med,2002,40(3):221-234.
[73] Yoo B C, Ku J L, Hong S H, et al. Decreased pyruvate kinase M2 activity linked to cisplatin resistance in human gastric carcinoma cell lines.[J]. Int J Cancer,2004,108(4):532-539.
[74] Ping S, Wang S, Zhang J, et al. Effect of all-trans-retinoic acid on mRNA binding protein p62 in human gastric cancer cells.[J]. Int J Biochem Cell Biol,2005,37(3):616-627.
[75] Zhang G, Wang G, Wang S, et al. Applying proteomic methodologies to analyze the effect of hexamethylene bisacetamide (HMBA) on proliferation and differentiation of human gastric carcinoma BGC-823 cells.[J]. Int J Biochem Cell Biol,2004,36(8):1613-1623.
[76] Shi P, Huang Z. Proteomic detection of changes in protein synthesis induced by lanthanum in BGC-823 human gastric cancer cells.[J]. Biometals,2005, 18(1):89-95.
[77] Banks R E, Dunn M J, Forbes M A, et al. The potential use of laser capture microdissection to selectively obtain distinct populations of cells for proteomic analysis-preliminary findings.[J]. Electrophoresis,1999,20(4-5):689-700.
[78] Lehner B, Tischler J, Fraser A G. Systems biology: where it's at in 2005.[J]. Genome Biol,2005,6(8):338.