Protein expression pattern distinguishes different lymphoid neoplasms

Immune-Proteome Profiling in Classical Hodgkin Lymphoma Tumor Diagnostic Tissue

In classical Hodgkin Lymphoma (cHL), immunoediting via protein signaling is key to evading tumor surveillance. We aimed to identify immune-related proteins that distinguish diagnostic cHL tissues (=diagnostic tumor lysates, n = 27) from control tissues (reactive lymph node lysates, n = 30). Further, we correlated our findings with the proteome plasma profile between cHL patients (n = 26) and healthy controls (n = 27). We used the proximity extension assay (PEA) with the OlinkTM multiplex Immuno-Oncology panel, consisting of 92 proteins. Univariate, multivariate-adjusted analysis and Benjamini–Hochberg’s false discovery testing (=Padj) were performed to detect significant discrepancies. Proteins distinguishing cHL cases from controls were more numerous in plasma (30 proteins) than tissue (17 proteins), all Padj < 0.05. Eight of the identified proteins in cHL tissue (PD-L1, IL-6, CCL17, CCL3, IL-13, MMP12, TNFRS4, and LAG3) were elevated in both cHL tissues and cHL plasma compared with control samples. Six proteins distinguishing cHL tissues from controls tissues were significantly correlated to PD-L1 expression in cHL tissue (IL-6, MCP-2, CCL3, CCL4, GZMB, and IFN-gamma, all p ≤0.05). In conclusion, this study introduces a distinguishing proteomic profile in cHL tissue and potential immune-related markers of pathophysiological relevance.

Proteome dynamics of cold-acclimating Rhododendron species contrasting in their freezing tolerance and thermonasty behavior

To gain a better understanding of cold acclimation in rhododendron and in woody perennials in general, we used the 2D-DIGE technique to analyze the rhododendron proteome during the seasonal development of freezing tolerance. We selected two species varying in their cold acclimation ability as well as their thermonasty response (folding of leaves in response to low temperature). Proteins were extracted from leaves of non-acclimated (NA) and cold acclimated (CA) plants of the hardier thermonastic species, R. catawbiense (Cata.), and from leaves of cold acclimated plants of the less hardy, non-thermonastic R. ponticum (Pont.). All three protein samples (Cata.NA, Cata.CA, and Pont.CA) were labeled with different CyDyes and separated together on a single gel. Triplicate gels were run and protein profiles were compared resulting in the identification of 72 protein spots that consistently had different abundances in at least one pair-wise comparison. From the 72 differential spots, we chose 56 spots to excise and characterize further by mass spectrometry (MS). Changes in the proteome associated with the seasonal development of cold acclimation were identified from the Cata.CA-Cata.NA comparisons. Differentially abundant proteins associated with the acquisition of superior freezing tolerance and with the thermonastic response were identified from the Cata.CA-Pont.CA comparisons. Our results indicate that cold acclimation in rhododendron involves increases in abundance of several proteins related to stress (freezing/desiccation tolerance), energy and carbohydrate metabolism, regulation/signaling, secondary metabolism (possibly involving cell wall remodeling), and permeability of the cell membrane. Cold acclimation also involves decreases in abundance of several proteins involved in photosynthesis. Differences in freezing tolerance between genotypes can probably be attributed to observed differences in levels of proteins involved in these functions. Also differences in freezing tolerance may be attributed to higher levels of some constitutive protective proteins in Cata. than in Pont. that may be required to overcome freeze damage, such as glutathione peroxidase, glutamine synthetase, and a plastid-lipid-associated protein.

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

Surfaceome of classical Hodgkin and non-Hodgkin lymphoma

PURPOSE

Classical Hodgkin lymphoma (cHL) is characterized by a low percentage of tumor cells in a background of diverse, reactive immune cells. cHL cells commonly derive from preapoptotic germinal-center B cells and are characterized by the loss of B-cell markers and the varying expression of other hematopoietic lineage markers. This phenotypic variability and the scarcity of currently available cHL-specific cell surface markers can prevent clear distinction of cHL from related lymphomas.

EXPERIMENTAL DESIGN

We applied the cell surface capture technology to directly measure the pool of cell surface exposed proteins in four cHL and four non-Hodgkin lymphoma (NHL) cell lines.

RESULTS

More than 1000 membrane proteins, including 178 cluster of differentiation annotated proteins, were identified and allowed the generation of lymphoma surfaceome maps. The functional properties of identified cell surface proteins enable, but also limit the information exchange of lymphoma cells with their microenvironment.

CONCLUSION AND CLINICAL RELEVANCE

Selected candidate proteins with potential diagnostic value were evaluated on a tissue microarray (TMA). Primary lymphoma tissues of 126 different B cell-derived lymphoma cases were included in the TMA analysis. The TMA analysis indicated gamma-glutamyltranspeptidase 1 as a potential additional marker that can be included in a panel of markers for differential diagnosis of cHL versus NHL.

Proteomics Based Identification of Proteins with Deregulated Expression in B Cell Lymphomas

Follicular lymphoma and diffuse large B cell lymphomas comprise the main entities of adult B cell malignancies. Although multiple disease driving gene aberrations have been identified by gene expression and genomic studies, only a few studies focused at the protein level. We applied 2 dimensional gel electrophoresis to compare seven GC B cell non Hodgkin lymphoma (NHL) cell lines with a lymphoblastoid cell line (LCL). An average of 130 spots were at least two folds different in intensity between NHL cell lines and the LCL. We selected approximately 38 protein spots per NHL cell line and linked them to 145 unique spots based on the location in the gel. 34 spots that were found altered in at least three NHL cell lines when compared to LCL, were submitted for LC-MS/MS. This resulted in 28 unique proteins, a substantial proportion of these proteins were involved in cell motility and cell metabolism. Loss of expression of B2M, and gain of expression of PRDX1 and PPIA was confirmed in the cell lines and primary lymphoma tissue. Moreover, inhibition of PPIA with cyclosporine A blocked cell growth of the cell lines, the effect size was associated with the PPIA expression levels. In conclusion, we identified multiple differentially expressed proteins by 2-D proteomics, and showed that some of these proteins might play a role in the pathogenesis of NHL.

Difference gel electrophoresis DIGE

Proteomics offers powerful technologies to assist in the discovery of targets for novel therapeutic agents, by allowing the investigation of changes in protein state between control and diseased tissue and biofluids. Difference gel electrophoresis coupled with mass spectrometry (DIGE/MS) is a technology used within proteomics that has demonstrated technical robustness and associated statistical confidence to enable successful identification of therapeutic targets.:

Molecular Pathogenesis of Hodgkin's Lymphoma: Increasing Evidence of the Importance of the Microenvironment

Hodgkin's lymphoma (HL) represents the most common subtype of malignant lymphoma in young people in the Western world. Most patients can be cured with modern treatment strategies, although approximately 20% will die after relapse or progressive disease. The histologic hallmark of the disease is the presence of the characteristic Hodgkin Reed-Sternberg (HRS) cells in classical HL and so-called lymphocyte-predominant (LP) cells in nodular lymphocyte-predominant HL. HL is unique among all cancers because malignant cells are greatly outnumbered by reactive cells in the tumor microenvironment and make up only approximately 1% of the tumor. Expression of a variety of cytokines and chemokines by the HRS and LP cells is believed to be the driving force for an abnormal immune response, perpetuated by additional factors secreted by reactive cells in the microenvironment that help maintain the inflammatory milieu. The malignant HRS and LP cells manipulate the microenvironment, permitting them to develop their malignant phenotype fully and evade host immune attack. Gene expression signatures derived from non-neoplastic cells correlate well with response to initial and subsequent therapies, reflecting their functional relevance. Recent biomarker studies have added texture to clinical outcome predictors, and their incorporation into prognostic models may improve our understanding of the biologic correlates of treatment failure. Moreover, recent preclinical and clinical studies have demonstrated that the tumor microenvironment represents a promising therapeutic target, raising hope that novel treatment strategies focused on the interface between malignant and reactive cells will soon emerge.

Application of MALDI imaging for the diagnosis of classical Hodgkin lymphoma

Hodgkin lymphoma (HL) is a distinctive lymphoma subtype characterized by rareness of tumor cells [Hodgkin's and Reed-Sternberg (HRS) cells in classical HL and lymphocytic and histiocytic cells in lymphocyte predominant HL] as well as the vast majority of the surrounding inflammatory-like cellular infiltrate. Still the onset of this highly variable disease is not completely understood. Proteome analysis can lead to the identification of potential proteins capable of elucidating malignant growth and survival in HL. Especially MALDI imaging could result in pinpointing differentially expressed proteins, which might represent potential marker molecules. In this study, we were able to distinguish between classical Hodgkin lymphoma and lymphadenitis with a sensitivity and specificity of 83.92 and 89.37%, respectively.

Mass spectrometry-based proteomics and its potential use in haematological research

In the last decade proteomics has made great progress reaching throughput and comprehensiveness comparable to genomics technologies. Mass spectrometry plays a key role in proteomics and has become an indispensable method for molecular and cellular biology because many cellular changes in response to internal or external stimuli can only be detected at the proteome level. Furthermore, different from genomics which depends on the availability of DNA or RNA, proteomics is not restricted to cellular samples, but also allows the analysis of biological fluids like serum, plasma or urine. This article provides an overview of the recent developments in proteomics techniques useful for haematological research.

Modulated T-complex protein 1 ζ and peptidyl-prolyl cis-trans isomerase B are two novel indicators for evaluating lymph node metastasis in colorectal cancer: Evidence from proteomics and bioinformatics

Lymph node metastasis (LNM) is an important indicator for systematic therapy, which could increase the survival of colorectal cancer (CRC) patients. However, effective clinical evaluation for LNM is still absent to date. In this study, protein expression profiles of CRC tissues were compared between patients with and without LNM. Based on average expression level, 12 proteins were found to be differentially expressed in the CRC tissues with LNM, whose discrimination reliability was confirmed by PCA. With stepwise linear discriminant analysis, T-complex protein 1 ζ subunit and peptidyl-prolyl cis-trans isomerase B (PPIB) were identified as two main contributors for separating CRC tissues with positive LNM from those negative ones in both original-grouped and cross-validated-grouped cases, which was also supported in subsequent linear support vector machine analysis. In addition, the expression alterations of the two proteins were verified by Western blot and immunohistochemistry. Functional studies also confirmed the role of PPIB in migration and invasion of cancer cells. Taken together, the down-regulated T-complex protein 1 ζ subunit and up-regulated PPIB were identified as two promising indicators for the clinical evaluation of LNM in CRC patients.

Optimizing the difference gel electrophoresis (DIGE) technology

Difference gel electrophoresis (DIGE) technology has been used to provide a powerful quantitative component to proteomics experiments involving 2D gel electrophoresis. DIGE combines spectrally resolvable fluorescent dyes (Cy2, Cy3, and Cy5) with sample multiplexing for low technical variation, and uses an internal standard methodology to analyze replicate samples from multiple experimental conditions with unsurpassed statistical confidence for 2D gel-based differential display proteomics. DIGE experiments can facilely accommodate sufficient independent (biological) replicate samples to control for the large interpersonal variation expected from clinical samples. The use of multivariate statistical analyses can then be used to assess the global variation in a complex set of independent samples, filtering out the noise from technical variation and normal biological variation thereby focusing on the underlying variation that can describe different disease states. This chapter focuses on the design and implementation of the DIGE methodology employing the use of a pooled-sample internal standard in conjunction with the minimal CyDye chemistry. Notes are also provided for the use of the alternative saturation labeling chemistry.

Treatment of missing values for multivariate statistical analysis of gel-based proteomics data

The presence of missing values in gel-based proteomics data represents a real challenge if an objective statistical analysis is pursued. Different methods to handle missing values were evaluated and their influence is discussed on the selection of important proteins through multivariate techniques. The evaluated methods consisted of directly dealing with them during the multivariate analysis with the nonlinear estimation by iterative partial least squares (NIPALS) algorithm or imputing them by using either k-nearest neighbor or Bayesian principal component analysis (BPCA) before carrying out the multivariate analysis. These techniques were applied to data obtained from gels stained with classical postrunning dyes and from DIGE gels. Before applying the multivariate techniques, the normality and homoscedasticity assumptions on which parametric tests are based on were tested in order to perform a sound statistical analysis. From the three tested methods to handle missing values in our datasets, BPCA imputation of missing values showed to be the most consistent method.

Proteomics analysis of Hodgkin lymphoma: identification of new players involved in the cross-talk between HRS cells and infiltrating lymphocytes

Hodgkin and Reed-Sternberg (HRS) cells in Hodgkin lymphoma (HL) secrete factors that interact with inflammatory background cells and may serve as biomarkers for disease activity. To detect new proteins related to pathogenesis, we analyzed the secretome of HRS cells. Proteins in cell culture supernatant of 4 HL cell lines were identified using 1DGE followed by in-gel trypsin digestion and LC-MS/MS. In total, 1290 proteins, including 368 secreted proteins, were identified. Functional grouping of secreted proteins revealed 37 proteins involved in immune response. Sixteen of the 37 proteins (ie, ALCAM, Cathepsin C, Cathepsin S, CD100, CD150, CD26, CD44, CD63, CD71, Fractal-kine, IL1R2, IL25, IP-10, MIF, RANTES, and TARC) were validated in HL cell lines and patient material using immunohistochemistry and/or ELISA. Expression of all 16 proteins was confirmed in HL cell lines, and 15 were also confirmed in HL tissues. Seven proteins (ALCAM, cathepsin S, CD26, CD44, IL1R2, MIF, and TARC) revealed significantly elevated levels in patient plasma compared with healthy controls. Proteomics analyses of HL cell line supernatant allowed detection of new secreted proteins, which may add to our insights in the interaction between HRS cells and infiltrating lymphocytes and in some instances might serve as biomarkers.

2D-PAGE maps analysis

Due to the low reproducibility affecting 2D gel-electrophoresis and the complex maps provided by this technique, the use of effective and robust methods for the comparison and classification of 2D maps is a fundamental tool for the development of automated diagnostic methods. A review of classical and recently developed methods for the comparison of 2D maps is presented here. The methods proposed regard both the analysis of spot volume datasets through multivariate statistical tools (pattern recognition methods, cluster analysis, and classification methods) and the analysis of 2D map images through fuzzy logic, three-way PCA, and the use of moment functions. The theoretical basis of each procedure is briefly introduced, together with a review of the most interesting applications present in recent literature.

Application of highly sensitive fluorescent dyes (CyDye DIGE Fluor saturation dyes) to laser microdissection and two-dimensional difference gel electrophoresis (2D-DIGE) for cancer proteomics

Proteome data combined with histopathological information provides important, novel clues for understanding cancer biology and reveals candidates for tumor markers and therapeutic targets. We have established an application of a highly sensitive fluorescent dye (CyDye DIGE Fluor saturation dye), developed for two-dimensional difference gel electrophoresis (2D-DIGE), to the labeling of proteins extracted from laser microdissected tissues. The use of the dye dramatically decreases the protein amount and, in turn, the number of cells required for 2D-DIGE; the cells obtained from a 1 mm2 area of an 8-12 microm thick tissue section generate up to 5,000 protein spots in a large-format 2D gel. This protocol allows the execution of large-scale proteomics in a more efficient, accurate and reproducible way. The protocol can be used to examine a single sample in 5 d or to examine hundreds of samples in large-scale proteomics.

Comprehensive identification of proteins in Hodgkin lymphoma-derived Reed-Sternberg cells by LC-MS/MS

Mass spectrometry-based proteomics in conjunction with liquid chromatography and bioinformatics analysis provides a highly sensitive and high-throughput approach for the identification of proteins. Hodgkin lymphoma is a form of malignant lymphoma characterized by the proliferation of Reed-Sternberg cells and background reactive lymphocytes. Comprehensive analysis of proteins expressed and released by Reed-Sternberg cells would assist in the discovery of potential biomarkers and improve our understanding of its pathogenesis. The subcellular proteome of the three cellular compartments from L428 and KMH2 Hodgkin lymphoma-derived cell lines were fractionated, and analyzed by reverse-phase liquid chromatography coupled with electrospray ionization tandem mass spectrometry. Additionally, proteins released by Hodgkin lymphoma-derived L428 cells were extracted from serum-free culture media and analyzed. Peptide spectra were analyzed using TurboSEQUEST against the UniProt protein database (5.26.05; 188 712 entries). A subset of the identified proteins was validated by Western blot analysis, immunofluorescence microscopy and immunohistochemistry. A total of 1945 proteins were identified with 785 from the cytosolic fraction, 305 from the membrane fraction, 441 from the nuclear fraction and 414 released proteins using a minimum of two peptide identifications per protein and an error rate of <5.0%. Identification of proteins from diverse functional groups reflected the functional complexity of the Reed-Sternberg proteome. Proteins with previously reported oncogenic function in other cancers and from signaling pathways implicated in Hodgkin lymphoma were identified. Selected proteins without previously demonstrated expression in Hodgkin lymphoma were validated by Western blot analysis (B-RAF, Erb-B3), immunofluorescence microscopy (Axin1, Tenascin-X, Mucin-2) and immunohistochemistry using a tissue microarray (BRAF, PIM1). This study represents the first comprehensive inventory of proteins expressed by Reed-Sternberg cells of Hodgkin lymphoma and demonstrates the utility of combining cellular subfractionation, protein precipitation, tandem mass spectrometry and bioinformatics analysis for comprehensive identification of proteins that may represent potential biomarkers of the disease.

Differentiation of tumour-stage mycosis fungoides, psoriasis vulgaris and normal controls in a pilot study using serum proteomic analysis

BACKGROUND

Serum proteomic analysis is an analytical technique utilizing high-throughput mass spectrometry (MS) in order to assay thousands of serum proteins simultaneously. The resultant 'proteomic signature' has been used to differentiate benign and malignant diseases, enable disease prognosis, and monitor response to therapy.

OBJECTIVES

This pilot study was designed to determine if serum protein patterns could be used to distinguish patients with tumour-stage mycosis fungoides (MF) from patients with a benign inflammatory skin condition (psoriasis) and/or subjects with healthy skin.

METHODS

Serum was analysed from 45 patients with tumour-stage MF, 56 patients with psoriasis, and 47 controls using two MS platforms of differing resolution. An artificial intelligence-based classification model was constructed to predict the presence of the disease state based on the serum proteomic signature.

RESULTS

Based on data from an independent testing set (14-16 subjects in each group), MF was distinguished from psoriasis with 78.6% (or 78.6%) sensitivity and 86.7% (or 93.8%) specificity, while sera from patients with psoriasis were distinguished from those of nonaffected controls with 86.7% (or 93.8%) sensitivity and 75.0% (or 76.9%) specificity (depending on the MS platform used). MF was distinguished from unaffected controls with 61.5% (or 71.4%) sensitivity and 91.7% (or 92.9%) specificity. In addition, a secondary survival analysis using 11 MS peaks identified significant survival differences between two MF groups (all P-values <0.05).

CONCLUSIONS

Serum proteomics should be further investigated for its potential to identify patients with neoplastic skin disease and its ability to determine disease prognosis.

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.

Plasma proteomics of pancreatic cancer patients by multi-dimensional liquid chromatography and two-dimensional difference gel electrophoresis (2D-DIGE): up-regulation of leucine-rich alpha-2-glycoprotein in pancreatic cancer

We investigated the aberrant expression of plasma proteins in patients with pancreatic cancer. High-abundance plasma proteins (albumin, transferrin, haptoglobin, alpha-1-antitrypsin, IgG and IgA) were depleted by use of an immuno-affinity column, and low-abundance ones were separated into five fractions by anion-exchange chromatography. The fractionated plasma proteins were subjected to 2D-DIGE with highly sensitive fluorescent dyes. The quantitative protein expression profiles obtained by 2D-DIGE were compared between two plasma protein mixtures: one from five non-cancer bearing healthy donors and the other from five patients with pancreatic cancer. Among 1200 protein spots, we found that 33 protein spots were differently expressed between the two mixtures; 27 of these were up-regulated and six were down-regulated in cancer. Mass spectrometry and database searching allowed the identification of the proteins corresponding to the gel spots. Up-regulation of leucine-rich alpha-2-glycoprotein (LRG), which has not previously been implicated in pancreatic cancer, was observed. Western blotting with an anti-LRG antibody validated the up-regulation of LRG in an independent series of plasma samples from healthy controls, patients with chronic pancreatitis, and patients with pancreatic cancer. Our results demonstrate the application of a combination of multi-dimensional liquid chromatography with 2D-DIGE for plasma proteomics and suggest the clinical utility of LRG plasma level measurement.

Proteome analysis of B-cell maturation

Proteins affected by anti-mIgM stimulation during B-cell maturation were identified using 2-DE-based proteomics. We investigated the proteome profiles of stimulated and nonstimulated Ramos B-cells at eight time points during 5 d and compared the obtained proteomic data to the corresponding data from DNA-microarray studies. Anti-mIgM stimulation of the cells resulted in significant differences (> or =twofold) in the protein abundance close to 100 proteins and differences in post-translational protein modifications. Forty-eight up- or down-regulated proteins were identified by mass spectrometric methods and database searches. The identities of a further nine proteins were revealed by comparing their positions to the known proteins in other lymphocyte 2-DE databases. Several of the proteins are directly related to the functional and morphological characteristics of B-cells, such as cytoskeleton rearrangement and intracellular signalling triggered by the crosslinking of B-cell receptors. In addition to proteins known to be involved in human B-cell maturation, we identified several proteins that were not previously linked to lymphocyte differentiation. The results provide deeper insights into the process of B-cell maturation and may lead to novel therapeutic strategies for immunodeficiencies. An interactive 2-DE reference map is available at http://bioinf.uta.fi/BcellProteome.

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.

Two-dimensional gel electrophoresis as tool for proteomics studies in combination with protein identification by mass spectrometry

The proteome analysis by 2-DE is one of the most potent methods of analyzing the complete proteome of cells, cell lines, organs and tissues in proteomics studies. It allows a fast overview of changes in cell processes by analysis of the entire protein extracts in any biological and medical research projects. New instrumentation and advanced technologies provide proteomics studies in a wide variety of biological and biomedical questions. Proteomics work is being applied to study antibiotics-resistant strains and human tissues of various brain, lung, and heart diseases. It cumulated in the identification of antigens for the design of new vaccines. These advances in proteomics have been possible through the development of advanced high-resolution 2-DE systems allowing resolution of up to 10 000 protein spots of entire cell lysates in combination with protein identification by new highly sensitive mass spectrometric techniques. The present technological achievements are suited for a high throughput screening of different cell situations. Proteomics may be used to investigate the health effects of radiation and electromagnetic field to clarify possible dangerous alterations in human beings.