Proteomic analysis of primary esophageal squamous cell carcinoma reveals downregulation of a cell adhesion protein, periplakin

Recent advances in two-dimensional electrophoresis (2-DE) such as fluorescent 2-D differential gel electrophoresis (2-D DIGE) has made it possible to detect and quantitate the critical changes involved in disease pathogenesis. We have previously identified novel proteins with altered expression in primary colorectal cancer using agarose 2-DE that has a higher loading capacity than immobilized pH gradient gel. The aim of this study is to identify novel proteins with altered expression in primary esophageal cancer using the powerful method of agarose 2-DE and agarose 2-D DIGE. Excised tissues from 12 patients of primary esophageal cancer were obtained. Proteins with altered expression between cancer and adjacent non-cancer tissues were analyzed by agarose 2-D DIGE and identified by mass spectrometry. Thirty-three proteins out of 74 spots with altered expression in tumors were identified. Among them, a 195-kDa protein, periplakin, was significantly downregulated in esophageal cancer, which was confirmed by immunoblotting. Immunohistochemistry showed that periplakin was mainly localized at cell-cell boundaries in normal epithelium and dysplastic lesions, while it disappeared from cell boundaries, shifted to cytoplasm, in early cancers and scarcely expressed in advanced cancers. These results suggest that periplakin could be a useful marker for detection of early esophageal cancer and evaluation of tumor progression.     

Proteomic analysis of infiltrating ductal carcinoma tissues by coupled 2-D DIGE/MS/MS analysis

There is a growing interest in protein expression profiling aiming to identify novel diagnostic markers in breast cancer. Proteomic approaches such as two-dimensional differential gel electrophoresis coupled with tandem mass spectrometry analysis (2-D DIGE/MS/MS) have been used successfully for the identification of candidate biomarkers for screening, diagnosis, prognosis and monitoring of treatment response in various types of cancer. Identifying previously unknown proteins of potential clinical relevance will ultimately help in reaching effective ways to manage the disease. We analyzed breast cancer tissues from five tumor and five normal tissue samples from ten breast cancer subjects with infiltrating ductal carcinoma (IDC) by 2-D DIGE using two types of immobilized pH gradient (IPG) strips: pH 3-10 and pH 4-7. From all the spots detected, differentially expressed (p < 0.05 and ratio > 2) were 50 spots. Of these, 39 proteins were successfully identified by MS, representing 29 different proteins. Ten proteins were overexpressed in the tumor samples. The 2-D DIGE/MS/MS analysis revealed an increase in the expression levels in tumor samples of several proteins not previously associated with breast cancer, such as: macrophage-capping protein (CAPG), phosphomannomutase 2 (PMM2), ATPase ASN1, methylthioribose-1-phosphate isomerase (MRI1), peptidyl-prolyl cis-trans isomerase FKBP4, cellular retinoic acid-binding protein 2 (CRABP2), lamin B1 and keratin, type II cytoskeletal 8 (KRT8). Ingenuity Pathway Analysis (IPA) revealed highly significant (p = 10(-26)) interactions between the identified proteins and their association with cancer. These proteins are involved in many diverse pathways and have established roles in cellular metabolism. It remains the goal of future work to test the suitability of the identified proteins in samples of larger and independent patient groups.     

Proteomic signatures for histological types of lung cancer

We performed proteomic studies on lung cancer cells to elucidate the mechanisms that determine histological phenotype. Thirty lung cancer cell lines with three different histological backgrounds (squamous cell carcinoma, small cell lung carcinoma and adenocarcinoma) were subjected to two-dimensional difference gel electrophoresis (2-D DIGE) and grouped by multivariate analyses on the basis of their protein expression profiles. 2-D DIGE achieves more accurate quantification of protein expression by using highly sensitive fluorescence dyes to label the cysteine residues of proteins prior to two-dimensional polyacrylamide gel electrophoresis. We found that hierarchical clustering analysis and principal component analysis divided the cell lines according to their original histology. Spot ranking analysis using a support vector machine algorithm and unsupervised classification methods identified 32 protein spots essential for the classification. The proteins corresponding to the spots were identified by mass spectrometry. Next, lung cancer cells isolated from tumor tissue by laser microdissection were classified on the basis of the expression pattern of these 32 protein spots. Based on the expression profile of the 32 spots, the isolated cancer cells were categorized into three histological groups: the squamous cell carcinoma group, the adenocarcinoma group, and a group of carcinomas with other histological types. In conclusion, our results demonstrate the utility of quantitative proteomic analysis for molecular diagnosis and classification of lung cancer cells.     

Differentially expressed cytosolic proteins in human leukemia and lymphoma cell lines correlate with lineages and functions

Identification of cytosolic proteins differentially expressed between types of leukemia and lymphoma may provide a molecular basis for classification and understanding their cellular properties. Two-dimensional fluorescence difference gel electrophoresis (DIGE) and mass spectrometry have been used to identify proteins that are differentially expressed in cytosolic extracts from four human leukemia and lymphoma cell lines: HL-60 (acute promyelocytic leukemia), MEC1 (B-cell chronic lymphocytic leukemia), CCRF-CEM (T-cell acute lymphoblastic leukemia) and Raji (B-cell Burkitt's lymphoma). A total of 247 differentially expressed proteins were identified between the four cell lines. Analysis of the data by principal component analysis identified 22 protein spots (17 different protein species) differentially expressed at more than a 95% variance level between these cell lines. Several of these proteins were differentially expressed in only one cell line: HL-60 (myeloperoxidase, phosphoprotein 32 family member A, ras related protein Rab-11B, protein disulfide-isomerase, ran-specific GTPase-activating protein, nucleophosmin and S-100 calcium binding protein A4), and Raji (ezrin). Several of these proteins were differentially expressed in two cell lines: Raji and MEC1 (C-1-tetrahydrofolate synthase, elongation factor 2, alpha- and beta-tubulin, transgelin-2 and stathmin). MEC1 and CCRF-CEM (gamma-enolase), HL-60 and CCRF-CEM (ubiquitin-conjugating enzyme E2 N). The differentially expressed proteins identified in these four cell lines correlate with cellular properties and provide insights into the molecular basis of these malignancies.     

Proteomics strategy based on liquid-phase IEF and 2-D DIGE: application to bone marrow mesenchymal progenitor cells

Global comparative proteomics is a promising new approach with broad application in basic and clinical biological science. Recent advances include the development of 2-D DIGE, a proteomic equivalent to mRNA differential display, in which differentially labeled samples are multiplexed and analyzed by high-resolution 2-DE. This study presents a new 2-D DIGE protocol, in which complex protein samples from normal and leukemic human bone marrow mesenchymal progenitor cells were used as model samples for a novel combination of liquid-phase IEF with 2-D DIGE. Using liquid-phase IEF, the normal and leukemic cells were pre-fractionated into five subproteomes after multiplexing but prior to DIGE. Under these conditions, 2-D DIGE resolved >5000 protein-containing spots within the pH range 4.6-7.0. Differential labeling combined with subsequent MALDI-MS/MS identified proteins that were differentially expressed in leukemic cells. This analysis mapped protein identities to 128 mesenchymal progenitor cell proteins with at least one unique peptide match at >95% confidence. Of these proteins, 72 (56%) were expressed more than 1.25-fold higher or lower in leukemic cells compared with normal cells (p<0.05). These data were used to infer gene ontology biological processes that may be altered in leukemic bone marrow mesenchymal progenitor cells.     

Proteomic analysis in clear cell renal cell carcinoma: identification of differentially expressed protein by 2-D DIGE

Renal cell carcinoma (RCC), the most common neoplasm affecting the adult kidney, is characterised by heterogeneity of histological subtypes, drug resistance, and absence of molecular markers. Two-dimensional difference gel electrophoresis (2-D DIGE) technology in combination with mass spectrometry (MS) was applied to detect differentially expressed proteins in 20 pairs of RCC tissues and matched adjacent normal kidney cortex (ANK), in order to search for RCC markers. After gel analysis by DeCyder 6.5 and EDA software, differentially expressed protein spots were excised from Deep Purple stained preparative 2DE gel. A total of 100 proteins were identified by MS out of 2500 spots, 23 and 77 of these were, respectively, over- and down-expressed in RCC. The Principal Component Analysis applied to gels and protein spots exactly separated the two sample classes in two groups: RCC and ANK. Moreover, some spots, including ANXA2, PPIA, FABP7 and LEG1, resulted highly differential. The DIGE data were also confirmed by immunoblotting analysis for these proteins. In conclusion, we suggest that applying 2-D DIGE to RCC may provide the basis for a better molecular characterization and for the discovery of candidate biomarkers.     

Toward a comprehensive quantitative proteome database: protein expression map of lymphoid neoplasms by 2-D DIGE and MS

Using 2-D DIGE, we constructed a quantitative 2-D database including 309 proteins corresponding to 389 protein spots across 42 lymphoid neoplasm cell lines. The proteins separated by 2-D PAGE were identified by MS and assigned to the expression data obtained by 2-D DIGE. The cell lines were categorized into four groups: those from Hodgkin's lymphoma (HL) (4 cell lines), B cell malignancies (19 cell lines), T cell malignancies (16 cell lines), and natural killer (NK) cell malignancies (3 cell lines). We characterized the proteins in the database by classifying them according to their expression level. We found 28 proteins with more than a 2-fold difference between the cell line groups. We also noted the proteins that allowed multidimensional separation to be achieved (1) between HL cells and other cells, (2) between the cells derived from B cells, T cells and NK cells, and (3) between HL cells and anaplastic large cell lymphoma cells. Decision tree classification identified five proteins that could be used to classify the 42 cell lines according to differentiation. These results suggest that the quantitative 2-D database using 2-D DIGE will be a useful resource for studying the mechanisms underlying the differentiation phenotypes of lymphoid neoplasms.     

2D differential in-gel electrophoresis for the identification of esophageal scans cell cancer-specific protein markers

The reproducibility of conventional two-dimensional (2D) gel electrophoresis can be improved using differential in-gel electrophoresis (DIGE), a new emerging technology for proteomic analysis. In DIGE, two pools of proteins are labeled with 1-(5-carboxypentyl)-1'-propylindocarbocyanine halide (Cy3) N-hydroxy-succinimidyl ester and 1-(5-carboxypentyl)-1'-methylindodi-carbocyanine halide (Cy5) N-hydroxysuccinimidyl ester fluorescent dyes, respectively. The labeled proteins are mixed and separated in the same 2D gel. 2D DIGE was applied to quantify the differences in protein expression between laser capture microdissection-procured esophageal carcinoma cells and normal epithelial cells and to define cancer-specific and normal-specific protein markers. Analysis of the 2D images from protein lysates of approximately 250,000 cancer cells and normal cells identified 1038 protein spots in cancer cell lysates and 1088 protein spots in normal cell lysates. Of the detected proteins, 58 spots were up-regulated by >3-fold and 107 were down-regulated by >3-fold in cancer cells. In addition to previously identified down-regulated protein annexin I, tumor rejection antigen (gp96) was found up-regulated in esophageal squamous cell cancer. Global quantification of protein expression between laser capture-microdissected patient-matched cancer cells and normal cells using 2D DIGE in combination with mass spectrometry is a powerful tool for the molecular characterization of cancer progression and identification of cancer-specific protein markers.     

Database of two-dimensional polyacrylamide gel electrophoresis of proteins labeled with CyDye DIGE Fluor saturation dye

CyDye DIGE Fluor saturation dye (saturation dye, GE Healthcare Amersham Biosciences) enables highly sensitive 2-D PAGE. As the dye reacts with all reduced cysteine thiols, 2-D PAGE can be performed with a lower amount of protein, compared with CyDye DIGE Fluor minimal dye (GE Healthcare Amersham Biosciences), the sensitivity of which is equivalent to that of silver staining. We constructed a 2-D map of the saturation dye-labeled proteins of a liver cancer cell line (HepG2) and identified by MS 92 proteins corresponding to 123 protein spots. Functional classification revealed that the identified proteins had chaperone, protein binding, nucleotide binding, metal ion binding, isomerase activity, and motor activity. The functional distribution and the cysteine contents of the proteins were similar to those in the most comprehensive 2-D database of hepatoma cells (Seow et al.., Electrophoresis 2000, 21, 1787-1813), where silver staining was used for protein visualization. Hierarchical clustering on the basis of the quantitative expression profiles of the 123 characterized spots labeled with two charge- and mass-matched saturation dyes (Cy3 and Cy5) discriminated between nine hepatocellular carcinoma cell lines and primary cultured hepatocytes from five individuals, suggesting the utility of saturation dye and our database for proteomic studies of liver cancer.     

2-D DIGE analysis of the budding yeast pH 6-11 proteome in meiosis

Meiosis is the cell division that generates haploid gametes from diploid precursors. To provide insight into the functional proteome of budding yeast during meiosis, a 2-D DIGE kinetic approach was used to study proteins in the pH 6-11 range. Nearly 600 protein spots were visualised and 79 spots exhibited statistically significant changes in abundance as cells progressed through meiosis. Expression changes of up to 41-fold were detected and protein sequence information was obtained for 48 spots. Single protein identifications were obtained for 21 spots including different gel mobility forms of 5 proteins. A large number of post-translational events are suggested for these proteins, including processing, modification and import. The data are incorporated into an online 2-DE map of meiotic proteins in budding yeast, which extends our initial DIGE investigation of proteins in the pH 4-7 range. Together, the analyses provide peptide sequence data for 84 protein spots, including 50 single-protein identifications and gel mobility isoforms of 8 proteins. The largest classes of identified proteins include carbon metabolism, protein catabolism, protein folding, protein synthesis and the oxidative stress response. A number of the corresponding genes are required for yeast meiosis and recent studies have identified similar classes of proteins expressed during mammalian meiosis. This proteomic investigation and the resulting protein reference map make an important contribution towards a more detailed molecular view of yeast meiosis.     

A proteomic approach to the identification and characterisation of protein composition in wheat germ

Proteome analyses were carried out on commercial wheat germ of mature grain from the biscuit-making wheat cultivar, Rosella. Wheat germ protein extracts were fractionated by two-dimensional gel electrophoresis across two different immobilised pH gradients: pH 4.0–7.0 and 6.0–9.0. A total of 612 individual protein spots were excised from the gels and characterised by peptide mass fingerprinting. From these analyses, 347 individual proteins were identified from protein sequence database interrogation, and 301 different types of protein were catalogued according to protein function. The remaining 265 protein spots gave poor or no matches to proteins in the databases and were not identified in this study. Six different classes of enzymes were identified in the germ, many of them having roles in the mobilisation of energy reserves for germination. Abundantly expressed enzyme classes include the oxidoreductases, transferases and hydrolases. A comparison was also made between the major protein classes expressed in the germ and protein classes expressed in the endosperm from previous proteomic work. This study contributes significantly to our knowledge of protein expression and heterogeneity in the germ of wheat grain and forms the basis for future studies in regard to the characterisation of proteins during the initial stages of germination.     

胃癌及癌旁组织定量比较蛋白质组学研究

为寻找胃癌特异的肿瘤标记物,用于胃癌临床诊断及药物治疗靶点的选择,本研究采用荧光差异显示凝胶电泳（DIGE）技术分离并筛选 Cy3、Cy5 及 Cy2 荧光素标记的胃癌及对应癌旁组织差异表达蛋白质,用基质辅助激光解吸电离飞行时间质谱（MALDI-TOF MS）或串联质谱技术进行鉴定并分析。结果共筛选出 33 个差异表达蛋白质点,其中 9 个蛋白质点在胃癌组织中上调,24 个蛋白质点下调。对 22 个蛋白质点采用质谱技术成功鉴定,突变结蛋白、锰超氧化物歧化酶、热休克蛋白 60等在胃癌中高表达,热休克蛋白 27、前列腺素 F 合酶、硒结合蛋白 1、锌指蛋白 160、微管蛋白 α6、真核生物翻译延伸因子 1 α1 等在胃癌组织中低表达,并筛选出 5 个未知蛋白。这些差异表达蛋白可望成为胃癌诊断的特异标记物,并与胃癌的发生、发展及预后等有关,为胃癌的诊断、发生机制的研究提供了新的思路。     

Discovering robust protein biomarkers for disease from relative expression reversals in 2-D DIGE data

This study assesses the ability of a novel family of machine learning algorithms to identify changes in relative protein expression levels, measured using 2-D DIGE data, which support accurate class prediction. The analysis was done using a training set of 36 total cellular lysates comprised of six normal and three cancer biological replicates (the remaining are technical replicates) and a validation set of four normal and two cancer samples. Protein samples were separated by 2-D DIGE and expression was quantified using DeCyder-2D Differential Analysis Software. The relative expression reversal (RER) classifier correctly classified 9/9 training biological samples (p<0.022) as estimated using a modified version of leave one out cross validation and 6/6 validation samples. The classification rule involved comparison of expression levels for a single pair of protein spots, tropomyosin isoforms and alpha-enolase, both of which have prior association as potential biomarkers in cancer. The data was also analyzed using algorithms similar to those found in the extended data analysis package of DeCyder software. We propose that by accounting for sources of within- and between-gel variation, RER classifiers applied to 2-D DIGE data provide a useful approach for identifying biomarkers that discriminate among protein samples of interest.     

Quantitative analysis of mitochondrial protein expression in methylmalonic acidemia by two-dimensional difference gel electrophoresis

Isolated methylmalonic acidemia (MMA) is a rare metabolic disease due to the deficient activity of L-methylmalonyl-CoA mutase (MCM). This mitochondrial enzyme converts L-methylmalonyl-CoA to succinyl-CoA using adenosylcobalamin (Adocbl) as cofactor. Isolated MMA is subdivided into five forms: mut MMA associated with MCM deficiency, three different defects related to mitochondrial Adocbl formation (cblA, cblB, and cblH), and cblD variant 2. We performed proteomic analysis on mitochondria from an individual with cblH/cblD disorder using 2-D DIGE to identify differentially expressed proteins in this disease. Comparative analysis of control/patient mitochondrial proteome allowed us to identify differential expression of 10 proteins. The most notable groups included proteins involved in apoptosis (cytochrome c), oxidative stress (manganese superoxide dismutase) and cell metabolism (succinyl-CoA ligase (GDP forming) and mitochondrial glycerophosphate dehydrogenase). Immunoblot analysis further validated 2-D DIGE results of two of these proteins in multiple MMA patients, suggesting that the differences in expression are a general effect in this disorder. It is feasible that the differential proteins identified in this study have a biological significance and might be related to the pathophysiology of MMA.     

Construction of a proteome profile and functional analysis of the proteins involved in the initiation of mouse spermatogenesis

Spermatogenesis is a complex process of terminal differentiation wherein mature sperm are produced. In the first wave of mouse spermatogenesis, different spermatogenic cells appear at specific time points, and their appearance is expected to be accompanied by changes in specific protein expression patterns. In this study, we used 2D-PAGE and MALDI-TOF/TOF technology to construct a comparative proteome profile for mouse testis at specific time points (days 0, 7, 14, 21, 28, and 60 postpartum). We identified 362 differential protein spots corresponding to 257 different proteins. Further cluster analysis revealed 6 expression patterns, and bioinformatics analysis revealed that each pattern was related to many specific cell processes. Among them, 28 novel proteins with unknown functions neither in somatic cells nor germ cells were identified, 8 of which were found to be uniquely or highly expressed in mouse testes via comparison with the GNF SymAtlas database. Further, we randomly selected 7 protein spots and the above 8 novel proteins to verify the expression pattern via Western blotting and RT-PCR, and 6 proteins with little information in testis were further investigated to explore their cellular localization during spermatogenesis by performing immunohistochemistry for the mouse testis tissue. Taken together, the above results reveal an important proteome profile that is functional during the first wave of mouse spermatogenesis, and they provide a strong basis for further research.     

Proteome expression changes among virulent and attenuated Neospora caninum isolates

Neospora caninum is a cyst-forming parasite that has been recognised worldwide as a cause of cattle abortion and neuromuscular disease in dogs. Variations in genetic profiles, behaviour in vitro, and pathogenicity have been established among N. caninum isolates. However, it is unclear which parasite factors are implicated in this intra-specific diversity. Comparative analysis of protein expression patterns may define the determinants of biological diversity in N. caninum. Using DIGE and MALDI-TOF MS techniques, we quantified and identified differentially expressed proteins in the tachyzoite stage across three N. caninum isolates: the virulent Nc-Liv and Nc-Spain 7 isolates, and the attenuated Nc-Spain 1H isolate. Comparison between Nc-Spain 7 and Nc-Spain 1H extracts revealed 39 protein spots that were more abundant in Nc-Spain 7 and 21 in Nc-Spain 1H. Twenty-four spots were also increased in Nc-Spain 7 and 12 in Nc-Liv. Three protein spots were more abundant in the Nc-Liv extracts than in the Nc-Spain 1H extracts. MS analysis identified 11 proteins differentially expressed that are potentially involved in gliding motility and the lytic cycle of the parasite, and oxidative stress. These differences could help to explain variations in behaviour between isolates and provide a better knowledge of mechanisms associated with virulence.