Epithelial Proteomics in Multiple Organs and Tissues - American

differences of epithelial proteomics between different cells, locations, and diseases. We focus on ... Epithelial cells are located in multiple organs...
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Epithelial Proteomics in Multiple Organs and Tissues: Similarities and Variations between Cells, Organs, and Diseases Hong Zhao,† Kenneth B. Adler,‡ Chunxue Bai,† Fadi Tang,§ and Xiangdong Wang*,†,‡ Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, China, Department of Cell Biology, College of Veterinary Medicine, North Carolina State University, and Department of Pulmonary Pharmacology, Hangzhou Medical College, Zhejiang University, China Received November 8, 2005

Epithelial cells play an important role in physiological and pathophysiological situations, with organ-, tissue-, type-, and function-specific patterns. Proteome analysis has been used to study epithelial-origin diseases and identify novel prognostic, diagnostic, and therapeutic markers. The present review compares the variation of sample preparation for epithelial proteomic analysis, search similarities, and differences of epithelial proteomics between different cells, locations, and diseases. We focus on specificity of proteomic markers for epithelial-involved diseases. Proteomic alterations in epithelial cell lines were mapped to understand protein patterns, differentiation, oncogenesis, and pathogenesis of epithelial-origin diseases. Changes of proteomic patterns depend on different epithelial cell lines, challenges, and preparation. Epithelial protein profiles associated with intracellular locations and protein function. Epithelial proteomics has been greatly developed to link clinical questions, e.g., disease severity, biomarkers for disease diagnosis, and drug targets. There is an exciting and attractive start to link epithelial proteomics with histology of clinical samples. From the present review, we can find that most of disease-associated investigation of epithelial proteomics has been focused on epithelial-origin cancer. There is a significant gap of epithelial proteomics between acute and chronic organ injury, inflammation, and multiple organ dysfunction. Epithelial proteomics will provide powerful information on the relationships between biological molecules and disease mechanisms. Epithelial proteomics strategies and approaches should become more global, multidimensional, and systemic. Keywords: epithelial cells • proteomics • differentiation • tumorigenesis • cancer • biomarkers

Introduction Epithelial cells are located in multiple organs/tissues in human body, responsible for multiple functions, e.g., absorption, transport, secretion, defense, and metabolism.1,93,94 The origins of epithelial cells in various organs/tissues depend on three major cell lineages during gastrulation, e.g., ectoderm to skin, mesoderm to epithelial linings of the body cavities and endoderm to epithelial linings of the digestive, respiratory, and urinary tracts, and urethra (Figure 1). The common structure of epithelial cells has microvilli, cilia, basal bodies, desmosomes, zonular occulens, and zonular adherens under light microscopy. Epithelial cells are categorized into simple, pseudostratified, transitional, and stratified epithelia in respective organs/tissues, as shown in Table 1, with morphological specificity (Figure 2). The epithelium has protective function and covers the surfaces: skin (air interface), mucosa (secretory liquid interface), and gland (intercellular interface). In addition to the organ-specific function, epithelial cells have been * To whom correspondence should [email protected]. † Fudan University. ‡ North Carolina State University. § Zhejiang University. 10.1021/pr050389v CCC: $33.50

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considered to have systemic biological coordination and responses in physiological and/or pathophysiological conditions. Recently, derangements in the formation or function of specialized structures in epithelial cells, tight junctions, have been proposed to play the crucial role in the development of multiple organ dysfunction, e.g., lung, liver, gut, and perhaps kidney, associated with the conditions as sepsis and acute lung injury syndrome that are caused by inflammatory processes.2 Further considerations on potential mechanisms of epithelial cells-involved development of multiple organ dysfunction were addressed in the Journal of Organ Dysfunction.3 Epithelial cells may be activated to produce a number of inflammatory mediators, e.g., oxygen free radicals, nitric oxygen, and cytokines, leading to the compromise of other cells or themselves in the organs. It is also possible that epithelial cells communicate with endothelial cells to initiate inflammatory responses together or alone. A number of interorgan signaling factors have been suggested to be responsible for the delivery of primary insults to the distant organs.4 Epithelial cells may also play as the receptors for those interorgan signaling, to accelerate the local inflammatory process. However, there is little known about epithelial bio-responses to the challenges, e.g., inflammation, cancer, and toxics. One of the most Journal of Proteome Research 2006, 5, 743-755

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Figure 1. Epthelial cells are initially developed from zygote a single cell after sperm, into the blastula a simple spherical ball of cells. During gastrulation, cell movements result in a massive reorganization of the embryo, into a multilayered organism: endoderm, mesoderm, and ectoderm. Endoderm, the most internal germ layer, forms the inner lining of the gastraintestinal and respiratory tracts and other internal gland organs, e.g., liver and pancreas. Ectoderm, the most exterior germ layer, forms skin, brain, the nervous system, and other external tissues. Mesoderm, the middle germ layer, forms muscle, the skeletal system, and the circulatory system. Morphological characters of epithelial cells can be changed along their locations in the organ/ tissue. For exaple, pulmonary epithelial cells vary from the pseudostratified columnar epithelia to the simpale squamour cells as pointed by the black arrow.

important approaches to understand epithelial biology and involvement in diseases is to investigate changes of intracellular elements during the response. Proteomic analysis is a powerful tool to investigate protein profiles of cells, biopsies and fluids, to explore protein-based mechanisms of human diseases, identify novel biomarkers for diagnosis, therapy, and prognosis of multiple diseases, and discover new targets for drug development.5-9,98-100 Proteomic approaches have also been applied to describe the proteomic profiling of epithelial cells and epithelial origin cancer and stroma, monitor molecular targeted therapy, measure intracellular signaling pathways in primary and metastatic cancer, and provide implications for diagnosis of the diseases.10 It is possible that the variation of proteomic profile of epithelial cells or their suborgans exists among their locations, disease types and phases, ages, and responses, although there is no such direct evidence to clarify such variation. Experimental study demonstrated that proteomic profiles varied between lung cell

Figure 2. Characteristics of epithelial cells in different organs and tissues. The common morphology of these cells includes the basal surface lied on the basement membrane, the apical surface facing the lumen. tight junctions helding cells together. The shape of epithelial cells vary between organs/tissues, e.g., A: the pseudostratified columnar epithelium of the trachea, B: stratified squamous keratinizing epithelium of the lip, C: the simple squamous epithelial line of the glomerulus, D: the simple cuboidal epithelium of thyroid gland follicles, E: the simple columnar epithelium of uterine gland, F: the simple cuboidal epithelium of renal collecting duct, G: the pseudostratified columnar epithelium of male urethra, H: the stratified cuboidal epithelium of sweat gland duct, I and J: the transitional stratified epithelium from the different parts of the bladder, and K: the simple columnar epithelium of gall bladder.

phenotypes isolated by different techniques,11 related to proteinprotein/protein-gene interactions, post-translational modifications, and cell dysfunction. Proteomic analysis can be useful for screening and selecting highly sensitive, specific proteins as biomarkers of drug-associated interstitial lung diseases.12 Most of published papers and reviews demonstrated the changes of protein profiles in epithelial cells in a certain organ, tissue, or disease.87-92 The present review emphasizes the epithelial cells as an intact system in the body, compares the variation of sample preparation for epithelial proteomic analysis, search similarities and differences of epithelial proteomics between different cells, locations and diseases, and focuses on specificity of proteomic markers for epithelial-involved diseases. We investigate potential links of the findings from epithelial proteomic research to clinical questions, finding, diagnosis and prognosis, and understand intra-epithelial signaling, consistence between genomic and proteomic appearance, and discovery of new targets. Variation of Sample Preparation for Proteomic Analysis. Protein Separation. There is still a great need to separate cellular proteins with high efficiency and to have one technol-

Table 1. Categories of Epithelial Cells Based on Histological Morphology and Respective Locations simple

pseudostratified

transitional

squamous

lungs (alveoli), capillary endothelium, lining of pleural cavity, pericardium, peritoneum, Bowman’s capsule (Kidney) Cuboidal follicle of thyroid gland, collecting ducts of kidney, salivary glands, pancreas columnar gall bladder surface, epithelium of male urethra stomach, Uterine glands (all phases), small intestine ciliated columnar trachea

oral (lip), pharynx, esophagus, anal canal, uterine, cervix, vagina, skin(keratinzed) ducts of sweat glands large excretory duct of salivary glands, parotid, submandibular sublingual

urinary bladder 744

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Epithelial Proteomics in Multiple Organs and Tissues

Table 2. Comparison of Topic Five Proteins of Epithelial Cells with High Spot Intensity among Different Sources, as Compared with Respective Controls (Folds) sourcesa

BDC (r17)

1

2

3

4

5

Thioredoxin peroxidase (454) NADH dehydrogenase (2.2) Glutaminase (2.8) CLL-associared antigen KW-1 (Hsp70) (48.1)

Stathmin (137)

Profilin 1 (34)

Hsp 90 (26)

Cofilin (25)

Glyoxalase (2.0)

Peroxiredoxin 3 (1.8)

Selenophosphate synthetase (1.6)

NOS2 (2.7)

Hsp-70 (2.2)

Annexin II (2.0)

Zinc finger protein 138 (46.6)

Mv1Lu-2h (r84)

Keratin 10 (2.4)

Phosphoglycerate kinase-1 (2.2)

SPLICE isoform IK7 DNA-binding protein Ikaros (LyF-1) (13.4) P59 protein (1.7)

Mv1Lu-24 h (r84)

Ubiquitin-like fusion protein An1b (2.5)

P59 protein (2.5)

TNG receptor supperfamily member XEDAR (28.8) Myosin regulatory light chain (1.7) Musashi-1 homologue (2.4)

Thioredoxin peroxidase (1.5) Cathepsin D (1.9) Hypothetical protein (12.2)

H1299 (r38)

TEF1δ (56)

Cytokeratin 8 (24)

Vimentin (17)

PCNA (9)

SW1573 (r38)

Cytokeratin 8 (42) TEF1δ (77) Cytokeratin 8 (68) TEF1δ (48)

TEF1δ (38)

Vimentin (29)

YB-1 (21)

Cytokeratin 8 (52) TEF1δ (59)

YB-1 (17) YB-1 (19)

Vimentin (13) PCNA (13)

Vimentin (8)

PCNA (6)

Nm23 (4)

hnRNP A2/B1 (4.7)

R-Enolase (3.6)

Hsp90R (2.7)

β-Tubulin (2.4)

T29H (r20)b

IMCD (r60) LSC (r43)

H23 (r38) H226 (r38) HBE4 (r38)

E9/E10 (r77)

Phosphoglycerate kinase-1 (2.2)

GFP (1.6)

Far upstream elementbinding protein (2.2) M-type pyruvate kinase B (5) PCNA (16) PCNA (11) Vimentin (10) M-type pyruvate kinase B (3) Aldolase A (1.5)

a BDC: breast ductal carcinoma; T29H: human ovarian epithelial cell lines transformed with oncogenic rasV12 allele. IMCD: the inner medullary collecting duct. LSC: lung squamous carcinoma. XEDAR: X-linked ectodysplsin-A2 receptor. b The paper only listed top five up-regulated enzymes involved in cellular redox balance of the 30 proteins identified (ref 20).

ogy to separate all types of proteins within the cell if possible, due to the limit of current methods (two-dimensional gel electrophoresis 2DGE, gel-free electrophoresis, and multidimensional chromatography) and the overlapping of physicochemical characteristics.10 Combination of multidimensional separation with mass spectrometry (MS/MS) could detect about 5838 unique peptides identified covering 1574 different proteins from human mammary epithelial cells (HMEC 184 AIL5), with an estimated 4% gene coverage of the human genome.13 It is basic but important that the study categorized identified proteins on the basis of intracellular location and biological process (Table 2). Although the number of 1000-3000 separated proteins by current techniques is high, it is still far from the estimated number of proteins in a cell about 50 000300 000.14,15 To improve the detection, identification, and characterization of low abundant proteins, centrifugal ultrafiltration for sample concentration and desalting, prior electrophoresis, was used in two different human breast cancer cell lines with highly invasive and a noninvasive capacities.16,17 The application of proteomics techniques combined with the additional cell lysate and extracted peptide concentration steps enhanced spectra quality for high confidence protein identification. Pretreated Cell Culture. Most studies on epithelial functional proteomics have been performed by using the cell line system where epithelial cells can be pretreated with stimulators or inhibitors. For example, protein profiles of growth-promot-

ing, growth-inhibiting, and pro-apoptotic signaling pathway have been investigated after epithelial cells incubated with growth factors or inhibitors.18 Study on functional proteomics can also concentrate on certain protein groups or families. The potential correlation between the expression of heat shock proteins (Hsps), a specific family of highly conserved proteins, and immunogenicity was investigated in renal cell carcinoma cell lines and cells immortalized by SV40LT transformation as normal kidney epithelium.19 Proteomic analysis of Hsps was performed after cells were treated with interferon-γ or autologus and allogeneic sera from cancer patients and healthy, an example for the design of immunization strategies to induce a potent antitumor response. Gene-Manipulated Cells. To investigate the influence of a certain gene on cell functional proteomics, protein profile can be addressed in epithelial cells with gene manipulation. To study potential mechanisms of Ras, a small GTP binding protein mutated in approximately 30% human cancer, in epithelial transformation, human ovarian epithelial cells were infected sequentially by retroviruses containing SV40 T/t antigens and hTERT genes to generate T29 cells, while the immortalized but nononcogenic T29 cells were further transformed by introducing an oncogenic H-RASV12 in a pLNCX retroviral vector to form the T29H cell line.20,21 Such a system seems to have a clear controlling condition to monitor the protein profiling induced by the certain gene for understanding the mechanism of gene-regulated signaling pathway. FuncJournal of Proteome Research • Vol. 5, No. 4, 2006 745

reviews tional proteomic analysis of a genetically defined cancer model merely provides a powerful approach toward systematically identifying cellular targets associated with oncogenic transformation. It needs well-characterized technology and wellcontrolled gene transformation, which may limit the application of such system. Cell Isolation Plus Culture. The initial study on proteomic analysis of the human ciliary axoneme was performed by isolating human bronchial epithelial cells from excess surgical tissue of normal subjects and cystic fibrosis patients.22 In this particular study, isolated epithelial cells were grown at an air/ liquid interface for 1-2 passages. Proteomic patterns of isolated and incubated ciliary axonemes were identified by 2D-PAGE, LC-MS/MS or multidimensional LC-MS/MS, including >1400 peptides and > potential axonemal proteins in total. It is considerable to characterize proteomics in pooled epithelial cells from both normal and cystic fibrosis samples, since it has described that epithelial biology can be altered as an important factor in the development of fibrosis.23,24 It should be aware that the manipulation of cell culture per se can influence cellular function and elements. The frequency of these axonemal proteins in different subjects may be helpful to clarify the potential variation between samples. LCM Isolation. In a study on the earliest progression of human breast cancer, Laser Capture Microdissection (LCM) was used to isolate highly selective epithelial cells from matched normal ductal/lobular units and ductal carcinoma in situ of the breast for proteomic analysis.17 This technique can select specific “normal” and “tumor” epithelial cells and compare proteomic patterns of these two type cells harvested from the same sample. This particular study demonstrated different protein expression or modification trends from the results of nucleic acid-based approaches.25 This technique needs the clear diagnosis from experienced pathologists to identify “normal” and “tumor” epithelial cells, although potential influence and interference from “tumor” cells to molecular metabolisms and function of “normal” cells could be hardly clarified. Combination of LCM-isolated cell types with fluorescent for protein derivatization could differentiate changes of protein profiles in highly selective cell populations.26 To compare other isolation methods, e.g., lysis-lavage and homogenization of whole lung, the microdissected airway homogenates yielded the fewest number of detectable protein spots.11 Reversed-phase protein microarrays combined with LCM have been suggested as optimal technology to map molecular networks of ovarian cancer epithelial cells isolated under direct microscopic vision from stained tissue sections.27 Approximately 25 000 cells were dissected for each case and lysed directly on the LCM cap with extraction buffer. One hundred arrays were printed on nitrocellulose-coated slides. An ovarian cancer reverse phase array was probed for active extracellular signal-regulated kinase (ERK) signaling using a phosphospecific antibody detected with a tyramide-based avidin/biotin amplification system. Phosphorylation-specific reference peptides were printed in a 12-point dilution curve on the bottom of the array for comparative, precise quantification of patient samples between arrays. Stained slides for the multiple phosphorylationspecific end points were scanned using Adobe Photoshop. Following total protein estimation with a Sypro Ruby stain, the intensity values of each antibody were normalized to total protein and dilution curves were generated using Microvigene software.27 Histograms could then be generated to compare alterations in cell signaling between the primary and metastatic 746

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samples. The amount of protein from captured cells may be limited and not be sufficiently accurate,28 whereas the amount of proteins obtained from -20 000 cells allows to perform hundreds of quantitative test using reverse phase microarrays.27,101,102 Subcellular Components: The nucleolus is a key organelle regulating the synthesis and assembly of ribosomal subunits and forms, cell growth and proliferation, and cellular senescence and stress responses. Unlike cytosolic organelles, nuclear bodies are not membrane bound. Andersen et al. performed a quantitative analysis of the proteome of human nucleoli harvested from HeLa cells,29 a human epithelial cell line from a fatal cervical carcinoma,30 using MS/MS-based organelle proteomics and stable isotope labeling amino acids in cell culture. In vivo fluorescent imaging techniques were used to directly compare endogenous protein changes measured by proteomics. Functional proteomics of transcription of nucleoli from HeLa cells were furthermore investigated after the isolated nucleoli were pretreated with transcription inhibitor (actinomycin D), RNA polymerase II inhibitor (DRB), and proteasome inhibitor (MG132). Such quantitative approach can be used for high throughput characterization of the flux of endogenous proteins through cellular organelles. Polarized epithelial cells were characterized by displaying compartmentized functions associated with differential distribution of transporters, structural proteins, and signaling molecules on their apical and basolateral surfaces.30 To further understand the specific protein profiling of apical microvilli of the epithelial cells, wheat germ agglutinin-agarose beads were used to isolated microvilli from mouse retinal pigment epithelia,31 which was suggested to be amenable for isolating microvilli in other epithelia. Specific Metabolites. Measurement of some specific metabolites needs the complement of proteomics. For example, conventional methodologies of proteomics have the limit of analyzing complex mixtures of isomeric nonesterified lipids due to their trace amounts, which lead to the development of MS/ MS-based lipidomic method as a complement to proteomic studies.32 Such methodology is important to be applied in cells rich with enantiomeric, regioisomeric and stereoisomeric bioactive lipids, e.g., intestinal epithelial cells. In rat intestinal epithelial cells transfected with cyclooxygenase-2 (RIES cells), the combination of electron capture atmospheric pressure chemical ionization with MS/MS were used to quantify enantiomers and regioisomers of diverse bioactive lipids derived from cyclooxygenase, lipoxygenase and reactive oxygen species.33 It was suggested that such targeted lipidomic approach could analyze bioactive lipids from other pathways, e.g., the cytochrome P450-derived epoxyeicosatetraenoic acids, LOXderived leukocytes and lipoxins, sphingomyelinase-derived ceramides, and ceramidase-derived sphingosines. The combination of in situ labeled cell surface proteins with proteomic analysis was found to increase the specificity of isolated plasma membrane and surface exposed regions of membrane proteins in HMEC (184 A1L5).34 Fluid Elements. Another method called the lysis-lavage is the combination of in situ lysing with bronchoalveolar lavage in animals.11 The lysis-lavage was claimed to selectively isolate proteins from Clara cells and ciliated cells and improve separation patterns and detection of low-abundance proteins. The critical steps in such technique were to inflate the lungs with an agarose solution in order to minimize the access to the parenchyma. Proteins were isolated directly from cells

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maintained in their natural microenvironment. However, such technique still lacks the specificity of targeting cell populations and the great limit to be used in human sample. Proteomic analysis of bronchoalveolar lavage fluid for the screening of biomarkers has been suggested to be the most common way of sampling the components of the epithelial lining fluid.35 Investigation of such fluid proteomic profiling is important to understand the pathogenesis of lung diseases, while it is still not clear that the portions/elements in the fluid are originally produced from the bronchial and/or alveolar epithelial cells. Similar challenge can be faced when addressing proteomic patterns of nipple aspirate fluids as potential biomarkers in the diagnosis of breast cancer.36 Isotope Labeling. It is widely accepted that the combination of stable-isotope labeling with LC-MS/MS can increase the sensitivity, proteomic coverage, and accuracy of quantitation. Isotope-coded affinity tags (ICAT) employs an isotopically distinct region flanked by iodoacetamide and biotin functionalities. The modi-fication and extraction of reduced Cyscontaining peptides (Cys-peptides) are measured using immobilized avidin chromatography. The method provides a highly accurate measurement due to stable isotope dilution techniques. The measured differences in protein expression correlated with yeast metabolic function under glucose-repressed conditions.96 A recent study demonstrated a new quantitative cysteinyl-peptide enrichment technology (QCET) with higher efficiency, greater dynamic range, and higher throughout in quantitative proteomics.37 QCET was developed on the basis of stable-isotope labeling of global tryptic peptides by trypsincatalyized 16O-18O exchange and the accurate mass and time tag approach in an in vitro system of nontumorigenic HMEC (A1L5). Briefly, epithelial cells are digested by trypsin and proteins are extracted. The resulting tryptic peptides are labeled by trypsin-catalyzed oxygen exchange using 16O- and 18Oenriched water, respectively. The two samples are combined, and cysteinyl-peptides are selectively captured and released using thiol-affinity resin. The enriched cysteinyl peptides are first analyzed by LC-MS/MS generating a PMT tag database that includes the calculated mass and normalized elution time for each identified peptide. The same peptide sample is analyzed by LC-FTICR, and peptides are identified and quantified as AMT tags by matching to the PMT tag database without the need for additional MS/MS analyses. The advantages of such technology are to focus on enrichment of cysteinylpeptides, have the reversible capture and release reaction, and provide higher sensitivity, protein coverage and throughout analysis, and more accurate quantitation. Variations of Epithelial Proteomics in Different Locations and Cell Types. It is difficult to compare the differentiation of proteomic profiling between fresh epithelial cells harvested from various organs/tissues, cell lines with different manipulations, and cells from different diseases. Protein profile varies among different preparations, isolations, and analyses, due to different aims and focuses of the investigation. Another issue to cause the difficulty of the comparison is that measurements and readouts are greatly different between studies. For example, two studies on proteomic analysis of HMECs (A1L5) were performed in the same research group.13,37 Cellular categorizations of identified proteins based on the predicted biological roles might be hardly compared between multidimensional proteomic analysis and QCET, due to the different treatments and categorizations. Even though the variation exists between

Figure 3. Cellular categorizations (%) of identified proteins based on the predicted biological roles between multidimensional proteomic analysis and quantitative cysteinyl-peptide enrichment technology. More obvious difference was noted in proteins related metabolism, protein biosynthesis, and protein metabolism as indicated by *.

multidimensional analysis and QCET, some categories of identified proteins are similar, as seen in Figure 3. An excellent study was performed to compare protein profiles of human lung nonsmall cancer cell lines (e.g., large cell carcinoma H1299, alveolar cell carcinoma SW1573, adenocarcinoma H23, squamous cell carcinoma H266), immortalized normal human bronchial epithelial cell line (HBE4-E6/E7), and primary human bronchial epithelial cells.38 The results demonstrated that expression of the cytokeratin 8 was only increased in cancer cell lines, as compared with both the normal cell line and primary cells which had a clear background. Expression of the proto-oncogene translation elongation factor 1δ (TEF1δ) was obviously increased in all cell lines, as compared with the primary cells (Table 2), although H23 and H226 had higher densities than HBE4-E6/E7. In opposite, expression of 14-3-3δ decreased in all cell lines as compared with the primary cells, while cancer cells had even lower expression of 14-3-3δ than the normal cell line.38 To investigate homology and differences in protein expression pattern between tumoral and nontumoral phenotypes, protein profiles of breast ductal infiltrating carcinoma cells and normal epithelial cells were measured.39 Of 58 identified proteins, twelve proteins were found differentially expressed in two cell lines: four (the ubiquitin carboxyl-terminal hydrolase isohyets, an isoelectronic variant of glutathione S-transferase, two unknown) were uniquely present in the neoplastic cell and eight in normal cells. In addition, 53 proteins displayed different relative expression levels between the two cell lines, of which 44 were more elevated in cancer cells and 9 in HB2 cells. HB2 cells displayed a polarized phenotype and responsive to contact inhibition, whereas 8701-BC cells had pleomophic morphology and overgrowth, forming typic domes. When comparing the difference of protein patterns between breast epithelial cell lines, CPS1 expressed only in luminal cells, while higher levels of ErbB-2 and ErbB-3 in C5.2, BT474, and SKBr3.40 Using a chemistry-based functional proteomics approach, another comparison of certain protease profiles was performed between normal, virus-infected and malignant human cells,41 including epithelial-origin carcinoma cell lines (HeLa from the cervix, CoLo from the colon, U1906 from the lungs, SH-SY-5Y from the brain, and HEK293 from the kidney) and hematopoietic cancer cell lines (K562 from erythroblasts, U937 from myeloblasts, Molt-3 from T cells, and HDLM-2, Namalwa and Journal of Proteome Research • Vol. 5, No. 4, 2006 747

reviews SU.DHL-4 from B cells). The family of ubiquitin (Ub)-specific proteases (USP) removes Ub from Ub conjugates and regulates a variety of cellular processes. Depending on tissue origin and stage of activation/differentiation, different USP activity profiles were revealed. The activity of specific USPs, including USP5, -7, -9, -13, -15, and -22, was up-regulated by mitogen activation or virus infection in normal T and B lymphocytes. Ub carboxyl-terminal hydrolase (UCH)-L1 was highly expressed in tumor cell lines of epithelial and hematopoietic cell origin but was not detected in freshly isolated and mitogen-activated cells, indicating the difference between organs/tissues, challenges, and diseases. UCH-L1 activities were higher in all seven neuroblastoma lines, whereas UCH-L3 was present in all other cell types. It reflects the importance of tissue origin, since UCHL1 is highly expressed in neurons and accounts for 1-2% of the total protein amount in brain.42 Up-regulation of this USP was a late event in the establishment of Epstein-Barr virusimmortalized lymphoblastoid cell lines and correlated with enhanced proliferation, but not epithelial cells. Variation of Proteomic Alterations between EpithelialAssociated Diseases. Cancer. Proteins identified from proteomic analysis of the earliest detectable form of breast cancer related to cytoskeletal architecture, chaperone function, the microenvironment, apoptosis, and genomic instability, in addition to those unconnected with breast cancer, e.g., the intracellular trafficking of membranes, vesicles, cancer preventative agents, and others. Of these proteins, stathmin related to microtubule destabilization and thioredoxin peroxidase to cytoplasmic antioxidant in epithelial cells of breast ductal carcinoma had the highest differential spot intensity (137 and 454% above, respectively), as compared to normal breast epithelia.17 This indicates that these cancer epithelia have strong capacities of motility and invasion and high resistance against the killing of oxygen free radicals. An enhanced antioxidation capability may constitute a common mechanism for tumor cells to evade apoptosis induced by oxidative stress at high levels of oxygen free radicals. The activation of Rassignaling pathways was found to increase reactive oxidative species tolerance in human ovarian epithelial cells with Rasmediated monogenic transformation.20 In addition, Ras also induced several other cellular pathways, including metabolism, redox balance, calcium signaling, apoptosis, and cellular methylation. These Ras-transformed cells may evade Fas-mediated apoptosis by down-regulating caspase 4 activation.21 Study on comparative proteomics of human lung squamous carcinoma demonstrated that increased expression of proteins identified (>10-folds above controls) included Hsp70 interaction protein (CLL-associated antigen KW-1 splice variant 1), zinc finger protein, EDA-A2 receptor (tumor necrosis receptor superfamily member X-linked ectodysplasin-A2 receptor), lymphoid transcription factor (LyF-1, SPLICE isoform IK7 of DANbinding protein Ikaros), hypothetical protein, G1/S-specific cyclin D2, and Mucin 5B precursor.43 Cell Transition. Epithelial to mesenchymal transitions have been considered as a crucial part in the pathogenesis of endometriosis, associated with pelvic pain, dysmenorrhoea, and subfertility in women of reproductive age. A number of signaling cascades may be involved in the process of epithelial to mesenchymal transitions. For example, phosphorylation by tyrosine kinases and/or threonine kinases regulates cell conformation, enzyme activities, and expression of genes and proteins.44 Signaling pathways include Src tyrosine kinases, Ras, Rac, Rho, mitogen-activated protein kinase, phosphatidylinosi748

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tol-3-kinase. Functional proteomics differentially phosphorylated and/or expressed during the transition were investigated in mesothelial cells in media conditioned with cells isolated from shed menstrual effluence.45 Proteins directly and indirectly associated with the cytoskeleton, signal transduction, redox state of the cells, and production of ATP were found to be phosphorylated and expressed during the transition. Of them, the remodeling of actin filments is most likely the central event of changes in mesothelial cell shape and motility. Proteins involved in cytoskeletal organization and energy metabolism can be phosphorylated and activated, leading to the cell transition. Stress. Proteomic approach was also used to identify early molecular targets in human epithelial lens cells after the challenge with oxidative stress.85 H2O2 exposure induced overexpression of cytoskeletal proteins (tubulin 1-alpha and vimentin), enzymes (phosphoglycerate kinase 1, ATP synthase beta, enolase alpha, nucleophosmin, heat-shock cognate 54 kDa protein, peroxiredoxin and glyceraldehyde 3-phosphate dehydrogenase). Helicobacter pylori infection leads to gastroduodenal inflammation, peptic ulceration, and gastric carcinoma. H. pylori-induced disease-specific protein expression in gastric epithelial cells included 14-3-3 protein alpha/beta, cullin homologue 3, alpha-enolase, and ezrin, related to cell proliferation, cell adhesion, and carcinogenesis.46 Understanding of Specificity of Proteomic Markers Associated with Clinical Events. Proteomics becomes a great tool to understand the protein profiling of multiple cells in both physiological and pathophysiological conditions. It has been highly emphasized that proteomics should be used to explore complexities of the disease and discover new elements responsible for and/or associated with the development of the disease.5 The system biology approach of integrating protein expression data with clinical data such as histopathology, clinical functional measurements, medical imaging scores, patient demographics, and clinical outcome provides a powerful tool for linking biomarker expression with biological processes that can be segmented and linked to disease presentation.47 Protein Specificity. When comparing changes in protein expression between normal breast epithelial cells and breast cancer cells, N-acetyltransferase (NAT-1) was found to increase consistently in invasive ductal and lobular breast carcinomas in a large number of samples (n ) 108), accompanied with overexpression of NAT-1 mRNA.48 NAT-1 is an enzyme involved in drug metabolism and cancer progression.49 Such target selected from proteomic analysis was confirmed to have proliferation-stimulating and apoptosis-preventing effects in the human breast epithelial cells (HB4a) transferred with NAT-1 gene.48 However, NAT-1 should be carefully considered as a therapeutic target, due to the potential association of NAT-1 polymorphisma with enzyme activity and cancer development and the organ/tissue specificity.49 Hsps can be induced in epithelial cells challenged by oxidative stress, chemical and physical exposure, ischemia, shock, inflammation, trauma, infection, and cancer.50,51 Proteomic analysis of Hsps in renal carcinoma epithelia indicated that Hsp27 could be paid an attention to as a potential marker for the diagnosis and status specific post-translational modification, since Hsp27 was only one of Hsp family showing significantly higher expression in renal carcinoma epithelia.19 It would be interesting to further investigate the specificity of epithelial Hsp27 among diseases or locations. In human

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Epithelial Proteomics in Multiple Organs and Tissues

pulmonary type II epithelial cells (A549) infected with the pneumovirus respiratory syncytial virus, Hsp70 and 60 were identified with cytoskeletal cytokeratins, RNA helicases, oxidantantioxidant enzymes, and the TAR DNA binding protein.52 It was proposed that such virus replication could induce a nuclear heat shock responses, cause nuclear domain 10 disruption and redistribute the component promyelocytic leukemia and speckled 100-kDa proteins to the cytoplasm. In addition, proteomic analysis demonstrated that both Hsp27 and 70 with aldose reductase, haem oxygenase-1 RB-crystal and ferritin were also up-regulated in rat lung epithelial cells treated with chemotherapeutic agent, as a potential mechanism by which the agent may reduce tumor growth through oxidative stress-associated apoptosis.53 14-3-3σ (Stratifin, HME1) was originally isolated as an epithelial-specific marker due to its expression only in epithelial cells and a significant hypo-expression in multiple epithelial cell carcinomas, e.g., breast, stomach, colon, lung, liver, pancreas, oral cavity, and vulva.54 The molecular chaperone 14-3-3σ has been considered as an example for using breast cancer proteomics to identify markers of potential clinical interest.55 In combination with a clear classification of tumors, proteomic analysis could furthermore demonstrate downregulated expression of 14-3-3σ in invasive bladder transitional cell carcinomas, particularly in lesions that were undergoing epithelial-to-mesenchymal conversion, but high expression in pure squamous cell carcinomas.56 There was an indirect evidence to show the variation of proteomic profile between different epithelium-origin tumors by evaluating proteomics of exosomes isolated from human malignant pleural effusions.57 Exosomes, member vesicles from endosomal origin, coined when the presence of “exfoliated membrane vesicles with 5′-nucleotidase activity” was first reported,58 are secreted by a variety of cells, e.g., hematopoietic, epithelial, and tumor cells as well as antigen-presenting cells. The use of exosomes engineered to prime the immune system against tumor antigens is a promising new arm of cancer immunotherapy, while exosomes released by the tumor itself may provoke a tolerogenic response.59 Study on proteomic analysis of exosomes demonstrated different protein profiles of exosomes between lung carcinoma, breast cancer, and mesothelioma, even though exosomes were harvested and isolated from the same location (pleural cavity) and material (effusion),57 as seen in Table 3, although the exact source of cells producing the pleural fluid was not clarified. The pituitary-derived antidiuretic hormone arginine vasopressin is important in the regulation of renal water excretion. Effects of vasopressin on proteomic profiling of the inner medullary collecting duct epithelial cells were investigated in the Brattleboro rat challenged with the vasopressin type 2 receptor-selective analogue DDAVP for 72 h.60 In this particular study, 43 proteins were regulated by vasopressin, of which 18 increased and 22 decreased. The number of identified proteins might be involved in regulatory effects of vasopressin in these cells, including e.g., nitric oxide-producing and consuming enzymes (arginase II, NADPH oxidase), vasopressin-escape mediators (adenylyl cyclase, GPCR kinase 4B), calcium-binding protein (annexin II), acute response proteins (Hsp-70, GRP78). These proteins may be considered as potential biomarkers for renal disease (Table 2), although the consistence with the response of human primary cells remains unclear. It should be emphasized that functional proteomic profiles in cancerorigin cell lines challenged with chemicals, stimulators or

Table 3. Scores of Proteomic Profile of Exosomes Isolated from Pleural Fluid of Patients with Breast Cancer, Lung Cancer and Mesothelioma, Briefly Summarized from Published Study (ref 57)a breast cancer

µ Ig chain C region µ Ig heavy chain constant region Acidic ribosomal protein actin β Albumin Bamacan protein β-fibrinogen precursor BTG1 protein Complement C1q Complement C4A precursor Complement factor H precursor Fibrinogen fragment Guanine nucleotide binding protein HLA-A30.3 precursor HSPC059 Hypothetical protein κ Ig chain KIAA MSTP043 Myosin heavy chain Nebulin PEDF protein kinase Spa thrombospondin 2 precusor TNF-induced protein Yotiao protein γ1 Ig γ3 Ig

lung cancer

mesothelioma

59 110

79 62

70 49

60

-

-

71 111 60 -

61 111 97 -

79

65 58 88

39 68 -

54 -

87

-

57

89 50

-

-

47

-

-

61 63 65 63 65 62 70 69 -

95 66 80 80 141 80

66 44 -

63

-

-

64 64 64

116 49

-

a BEAS-2B cells are human bronchial epithelial cells, transformed by SV40 T-antigen.

inhibitors may appear different from primary cancer cells or normal cells, since experimental study on effects of the chemical carcinogen promoter on CNE2 cell proteomics demonstrated that the promoter could induce those cells to antiproliferation and to apoptosis,61 different from the clinical finding.62 Such study may provide new clues to understand epithelial responses to those challenges and the molecular mechanisms of mutagenesis and carcinogenesis, as potential effects of specific stimuli on protein changes were investigated in human amnion epithelial cells.63 Clinical Relevance. Study on comparison of protein profiles between normal and malignant pancreatic ductal epithelial cells using combination of LCM and LC-MS/MS found that nine proteins expressed consistently different, of which five had higher expression and four had lower in cancer cells.28 In those overexpressed proteins, S100A6 a low molecular mass (10 kDa) Ca2+ binding protein was identified and further validated by immunohistological analysis. Potential rational of the incidence of S100A6 expression and the severity of the disease was investigated in well differentiated tumor, moderately differentiated tumor, or poorly differentiated tumor. The incidence of S100A6 in both cytoplastic and nuclear staining was signifiJournal of Proteome Research • Vol. 5, No. 4, 2006 749

reviews cantly higher in moderately (81% and 77%) and poorly differentiated pancreatic cancer (81% and 72%), as compared with the normal (16% and 11%, p < 0.05 or less, respectively), rather than well differentiated tumor. When comparing proteomic profiles of the patient-matched undissected bulk tumor lysates from patients with invasive ovarian cancers, noninvasive, low malignant potential ovarian tumors), 23 proteins were consistently differentially expressed between the low malignant potential and invasive ovarian tumors,86 although the number of patients was limited. Thirteen were uniquely present in the invasive ovarian cancer cases and absent or underexpressed in the low malignant potential. 52 kDa FK506 binding protein, Rho G-protein dissociation inhibitor (RhoGDI), and glyoxalase I were uniquely overexpressed in invasive human ovarian cancer when compared to the low malignant potential form of this cancer.86 It indicates that the direct comparison of LCM generated proteomic profiles of different stage of cancer may more directly generate important markers for early detection and/or therapeutic targets unique to the invasive phenotype. Tissue proteomic analysis found a protein with an average m/z of 24 782.56 ( 107.27 that was correlated with the presence of prostate carcinoma.64 The origin of this protein, PCa-24, was derived from the epithelial cells of the prostate. PCa-24 expression was detected in 16 of 17 (94%) prostate carcinoma specimens but not in paired normal or benign prostatic hyperplasia specimens. It was suggested that PCa-24 may be useful a marker for prostate carcinoma. Importantly, this particular study tried to correlate one of overexpressed proteins identified by proteomic analysis with the severity and progression of the disease, although not patterns of proteomic profiles. It would be even more significant if the study extend the comparison into patient prognosis and reoccurrence. By using LCM and reversed-phase protein array technology, proteomic profiles of prostate epithelial cancer were analyzed in phosphorylation-specific endpoints of cell signaling pathways associated with cell pro-survival, mitogenic, apoptotic, and growth regulation.65 Wong et al. developed a simple proteomic scoring derived from proteomic patterns bound to the protein-biochips.66 The scoring system was validated to identify cervical cancer from noncancer cohorts with a sensitivity of 87%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 86% for the test population. It would be exciting to combine such scoring system with the incidence of target proteins in the tissue to evaluate the significance of proteomic patterns and disease severities, with different locations of epithelial cells and types of disease to determine the specificity of readouts, and with clinical measurements to imply the importance for diagnosis and prognosis. Using microarrays of complementary DNA, gene-expression profiles were investigated in more than 50 specimens from normal adjacent prostate, benign prostatic hyperplasia, localized prostate cancer, and metastatic, hormone-refractory prostate cancer and three common prostate-cancer cell lines.67 Two of these genes-hepsin (a transmembrane serine protease) and pim-1 (a serine/threonine kinase) at the protein level were further measured using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. The integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathologic data has been suggested as a powerful approach to molecular profiling of human cancer. The study explored 750

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Zhao et al.

prognostic biomarkers in prostate cancer using microarrays of cDNA and tissue proteins. Although there is an increasing evidence to show alterations of epithelial proteomic profiles in pathophysiological conditions, it is important to be aware of the great need for machanism-based clinical studies. Experimental Impacts. An effort of linking proteomic measurements with disease-related changes was made in fractions prepared from distal colon of rats treated with the colonotropic carcinogen.68 Alterations in protein profiles were associated with the presence of aberrant crypt foci, hyperplasia and dysplasia, microanatomical changes, and metabolic changes in rat colon, indicating a potential role in the identification of pre-pathological features preceding colon tumorigenesis. Fehniger et al. performed an excellent experimental study to mimic antigen-associated pulmonary asthma in mice and to correlate the histological features of the dynamic pulmonary environment to the changes in protein expression in an experimental model of allergic airway inflammation.69 This particular study provided a clear picture of morphological selection for each studied area and linked proteomic analysis with pathological and morphometric analysis. Although the question may be asked how the animal model is associated with human disease, the study did compare control and allergen-challenged lung compartments to determine global protein expression patterns using 2D-gel electrophoresis and subsequent spot identification by MS/MS. The study provided new information of the complexity of the submucosa/epithelium interface and the mechanisms behind the transformation of airway epithelium from normal steady states to functionally activated states. It would be useful to translate such strategy and philosophy of disease-orientated proteomics in the experiment into proteomic studies in clinic. Signaling Pathway. Protein profile with the activity of signaling pathways in patient tissue has been concentrated because the tumor-host microenvironment influences the cellular proteome. A technology, rapid affinity capture of signaling proteins (GRASP), was developed to investigate the activity of signaling pathways from patient-derived ovarian carcinomas and benign epithelial surfaces.70 During the progression from benign ovarian epithelium to invasive carcinoma, there is loss of repression of Rho A as evidenced by its dissociation from its inhibitor. GRASP is more informative than simply profiling transcript or protein levels, coupled with MS/ MS to identify a protein-binding partner of the inhibitor. On the other hand, the reverse phase protein array immobilizes the whole repertoire of patient proteins that represent the state of individual tissue cell populations undergoing disease transitions, with a high degree of sensitivity, precision, and linearity. It makes possible to quantify the phosphorylated status of signal proteins in human tissue cell subpopulations. Using this novel protein microarray, the state of pro-survival checkpoint proteins was longitudinally analyzed at the microscopic transition stage from patient matched histologically normal prostate epithelium to prostate intraepithelial neoplasia and then to invasive prostate cancer.71 Cancer progression was associated with increased phosphorylation of Akt (P < 0.04), suppression of apoptosis pathways (P < 0.03), as well as decreased phosphorylation of extracellular signal-related kinase (P < 0.01), as compared with the matched normal cells. At the transition from histologically normal epithelium to prostate intraepithelial neoplasia, there was a statistical significance of activation of Akt and a concomitant suppression of downstream apoptosis pathways, leading to the transition into invasive carcinoma.

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Epithelial Proteomics in Multiple Organs and Tissues

Furthermore, increased activation of glycogensynthase kinase 3β a known substrate of AKT and decreased activation of protein kinase C-a were found to be involved in a higher degree in prostate cancer.65 In breast epithelial cell system stimulated with the ErbB-specific growth factor heregulin β1, proteomic analysis demonstrated ErbB-2 overexpression resulted in a combination of increased and temporal MAPK signaling, increased ErbB-related autocrine signaling and cdk activity thorugh up-regulation of cyclin D1 and CCND2 and downregulation of cdk inhibitors, inhibition of basal IFN signaling, and reduced cellular adhesion.40 Other Related Markers. It is possible that there is a common appearance (either up- or down-regulation) of some proteins identified from proteomic analysis of epithelial cells in multiple organs/tissues, cell lines and diseases, although the information on a specific protein correlated to multiple tasks remains limited. For example, the expression of vimentin, an intermediate filament protein implicated the tumor phenotype, has been found to be changed in many types of epithelial cells and diseases.38,72 The expression of Vimentin varies between epithelial cells and diseases. Up-regulation of vimentin was considered as one of lung cancer markers,73 while downregulation was noted in the conversion of tumorigenic prostate epithelial cells into slow growing and less aggressive cells.72 Vimentin was found to participate in the epithelial-mesenchymal transition of breast epithelial cells during the development of cell motility and metastatic capacity.74 Vimentin-positive tumor cells were found in 35% of adenocarcinomas and 88% of squamous cell carcinomas.75 In addition to the change of vimentin in cancer epithelial cells, cellular mislocalization of vimentin with galectin-1 and sorcin was also noted in tubular epithelial cells from polycystic kidney disease.76 While gapjunction structural gene-regulated tumorigenicity of neoplastic mouse lung epithelial cell line had higher expression of hnRNP A3/B1 and R-Enolase,77 rather than vimentin. Similarity between Genomic and Proteomic Changes. The study on a comparison of genomic and proteomic profiling in human bronchial epithelial cells demonstrated that expression of ERK3 genes increased and proteins decreased 4 h after the challenge with toxic metals, while gene expression of RSK1, PKACa, and PBBa/akt1 was changed similar to protein expression.78 Another study found that six genes coupling with proteins identified by mass spectrometry were successfully amplified from corresponding cDNA in both control and challenged samples using specific primers.61 In functional proteomic analysis of bronchial epithelial immortalized cells and malignant transformation cells, expression of Maspin protein was down-regulated in malignant transformation cells consistent with mRNA expression of Maspin,79 although there was information on other 1500 expressed proteins. It was suggested that altered expression of Maspin at transcription and translation levels might be involved in carcinogenesis of lung.79 Even although there are evidence of consistence between genomic and proteomic profiles, protein microarrays can be used to profile the working state of cellular signal pathways in a manner not possible with gene microarrays since posttranslational modifications cannot be accurately portrayed by global gene expression patterns alone.80 Partial consistence of expression of genes and proteins was noted in prostate epithelial cancer using microarrays of complementary DNA and tissue proteins.67 To validate mRNA changes by monitoring changes at the protein level using a parallel proteomics strategy, one

study found a high correlation (R ) 0.656) between transcription and translation in response to overexpression of the ErbB-2 receptor tyrosine kinase in a model mammary luminal epithelial cell system.40 2

One study was to aim at investigating the similarities and differences of expression patterns of genes and proteins between secretory epithelial cells and basal cells harvested from benign prostate gland.81 In this particular study, basal cells were selectively captured using an immuno-laser capture microdissection approach, and proteins were identified using surfaceenhanced laser desorption/ionization time-of-flight mass spectrometry, and genes were measured using microarrays. Results from that study demonstrated important information that expressed protein peaks of the basal cells were 1.1 and 1.2 kDa with two peaks, the whole glands were 0.96 with one, and the secretory cells had slight expression. There was a difference of gene expression patterns between basal cells and secretory cells, which was considered due to the variation of the total amount of RNA recovered from cells.81 However, the exact differences of genes and proteins between these two cells remains unclear, since these genes and proteins were not identified and categorized. The similarity between mRNA and proteins should be furthermore clarified in epithelia with a defined challenge and in the certain condition of 2D gel covering the sizes of mRNA corresponding proteins. It has been considered that gene expression profiles describe the transcriptional state of the cell, but not directly reflect the amount of protein profiles, due to huge potential combinations of gene product interactions.103 The relation between genomic and proteomic profiles depends on rates of translation and post-transcriptional modification, and on rates of protein decay, a process that the molecule is actively degraded or transformed. However, when identifying proteins by the molecular weight predicted from the gene, intra- and interspecies variation of the molecular weight was noted to be due to changes in the amino acid sequence of the protein, rather than to co- or post-translational modification.104 In other cells (neutrophils), it seemed that the similarity between mRNA transcript and protein expression changes varies on the basis of cell status and challenges.100 For example, poor concordance between mRNA transcript and protein expression changes was noted in exposure to lipopolysaccharide.105 In induced differentiation of cells, there is a much stronger correlation suggesting that a substantial proportion of protein change is a consequence of changed mRNA levels, rather than posttranscriptional effects.106 Discovery of New Targets. Transforming growth factor-β1 (TGFβ1) is involved the regulation of a wide variety of processes from development to pathogenesis, e.g., embryonal development, angiogenesis, immune response, tissue remodeling, fibrosis, inflammation, and cancer.82,83 Proteomic analysis is widely used to identify new targets induced by TGFβ1. Rapid and prolonged changes in proteomic profiling were investigated after human lung epithelial cells (Mv1Lu) for 2 and 24 h.84 TGFβ1-affected 38 identified proteins are associated with regulation of immune response, apoptosis, signaling, metabolism, and DNA repair. Proteins mostly affected by TGFβ1 and identified by PMF had two patterns of changes: rapid response (increase at 2 h and decrease at 24 h: keratin10, GFAP, myosin regulatory light chain, Rad51) and consistent response (increase at both 2 and 24 h: phosphoglycerate kinase-1, musashi-1 Journal of Proteome Research • Vol. 5, No. 4, 2006 751

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Zhao et al.

Table 4. Number of Epithelial Cell Lines Used for Proteomic Analysis organs

sources

kidney

H-renal cell carcinoma

lungs

H-normal kidney epithelia kidney carcinoma H-lung epithelial cells H-bronchial epithelial cells

alevolar type II epithelial cells

large cell lung cancer lung adenocarcinoma squamous cell carcinoma primary human normal bronchial epithelial cells small lung cancer cells H-surface ovarian epithelial cells H-nontumorigenic human mammary epithelial cell line breast cancer cell lines

codes

MZ1257RC MZ1940RC MZ2733RC MZ2733NN HEK293 Mv1Lu MCF7 MDA-MB-468 BEAS-2b BEP2D HBE4-E6/E7 A549 SW1573 E10 E9 E9-2 E9-41 H1299 H23 H226 NHBE-8917

studies

resp to IFNresp to IFN+ resp to IFN+ SV40LT transformation check more

immortalized or malignant transformated immortalized

refs

19 19 41 84

ATCC ATCC CC Harris

ATCC ATCC tumorigenic-, with GJIC tumorigenic+, GJIC deficient tumorigenic-, GJIC deficient vector control, TumorigenicATCC ATCC Cambrex

U1906 T29 SV40 T/t and telomerase T29H oncogenic rasV12 allele breast HMEC 184 Finite lifespan MCF7 MCF7 Jun BT474 SKBr3 MDA-MB-361 MB-435 MB-453 SUM159 SUM185 C3.6 overexpressing Erb B2 C5.2 human breast ductal infiltrating 8701-BC carcinoma-derived cell line human mammary epithelial HB2 cell line mammary luminal epithelial HB4a SV40 large T antigen cells Lum878 immortalized prostate human nonneoplastic P69SV40Tag SV40 large T antigen prostate epithelial cells immortalized human prostate epithelial M12 well-characterized tumorigenic cancer cells and metastatic subline of P69SV40Tag M12 (F6) introduction of an intact chromosome 19 into M12 cells cervix a fatal cervical carcinoma HeLa cells transformed by human papillomavirus 18 nose nasopharyngeal carcinoma CNE2 stomach human gastric epithelial cells AGS adenocarcinoma colon colonic carcinoma CoLo brain brain epithelial cancer cells SHsSY-5Y eyes human epithelial lens cells CD5A others human amnion epithelial FL cells transfected by human cells CYP1A1 full-length cDNA ovarian

suppliersa

specificities

metal toxicity Maspin exp

78 79

38 virus-infection 52 38 77 77 77 77 38 38 38 38

41 20,21 20,21 13 ATCC

Heregulin β1

40

Dr. Stephen Ethier

Heregulin β1

40 40

Dr. Michael O’Hare

Heregulin β1

40 72 72

72

16,17 Xiangya Med. College chem toxic ATCC H. pylori Bristol Eye Bank

61 47 41 41 85 63

ATCC: American Type Culture Collection.

homolog, ubiquitin-like fusion protein An1b, far upstream element-binding protein, and p59 protein), as shown in Table 2. HeLa cells are the classic example of an immortalized cell line transformed by human papillomavirus 18 (HPV18).30 HeLa 752

Journal of Proteome Research • Vol. 5, No. 4, 2006

cells are adherent cells which maintain contact inhibition in vitro, i.e., as they spread out across the culture flask, when two adjacent cells touch, this signals them to stop growing. Loss of contact inhibition is a classic sign of oncogenic cells, i.e., cells which form tumors in experimental animals. Such cells not only

reviews

Epithelial Proteomics in Multiple Organs and Tissues Table 5. Categorization of Identified Proteins in Human Mammary Epithelial Cells (what is the cell types) (r13,r29) intracellular locations

%

cell junction cytoplasm cytoskeleton er extracellular Golgi membrane mitochondrion nuclear membrane nucleus others ribosome unknown vesicle coat

0.7 25.7 10.4 1.5 2.0 0.9 10.3 6.2 0.6 15.7 1.6 5.2 18.4 0.8

intracellular protein function

%

cellular processes coenzymes and prosthetic group metabolism cytoskeleton organization and biogenesis DNA metabolism Energy pathways and metabolism hypothetical or unknown lipid metabolism nucleotide and metabolism protein biosynthesis protein catabolism transcription and RNA modification transport others

11.4 0.5 8.5 3.2 1.3 17.9 1.9 2.3 12.4 5.0 8.9 8.8 17.9

form a monolayer in culture but also pile up on top of one another in foci. About 489 endogenous nucleolar proteins were characterized in response to three different metabolic inhibitors that each affected nucleolar morphology.29 Proteins that are stably associated, such as RNA polymerase I subunits and small nuclear ribonucleoprotein particle complexes, exit from or accumulate in the nucleolus with similar kinetics, whereas protein components of the large and small ribosomal subunits leave the nucleolus with markedly different kinetics. Summary and Future Indication. Epithelial cells play an important role in the bidirectional interchange of chemical and mechanical signals with the microenvironment, with organ-, tissue-, type-, and function-specific patterns. Proteome analysis as a powerful tool is widely used for the study of epithelialorigin diseases and for identifying novel prognostic, diagnostic, and therapeutic markers. Many epithelial cell lines have been used as an in vitro system to investigate proteomic alterations (Table 4) to understand protein patterns, differentiation, oncogenesis, and pathogenesis of epithelial-origin diseases. Changes of proteomic patterns depend on different epithelial cell lines, challenges, and preparation (Table 2). Proteomic analysis of epithelial cells describes protein profiles associated with intracellular locations, intracellular protein function and intranucleolar protein function (Table 5), although the information remains limited. It is important to understand potential variations and similarities between epithelia, locations, preparations, and diseases. Epithelial proteomics has been greatly developed to link clinical questions, e.g., disease severity, biomarkers for disease diagnosis, and drug targets. There is an exciting and attractive start to link epithelial proteomics with histology of clinical samples. From the present review, we can find that most of disease-associated investigation of epithelial proteomics has been focused on epithelial-origin cancer, tumorigenesis, and cell differentiation, and some on stress and infection. There is a significant gap of the investigation between epithelial proteomics, acute and chronic organ injury, inflammation, and multiple organ dysfunction, a systemic consequence of acute and chronic diseases.95 As a common challenge in proteomic and genomic research, the statistical analyses and assumptions of epithelial proteomic profiles need to be clarafied and standardized, comparable with the analysis of clinical and preclinical studies. There is a great need to identify epithelial proteomics between organs/tissues and clarify protein-specific

intranucleolar protein function

%

cell-cycle proteins chaperones chromatin-related factors DNA repair proteins DNA-binding proteins DNA-replication proteins HnRNP kinases/phosphatases other translation factors others potential contaminates ribosomal proteins RNA helicase RNA polymerase RNA-binding proteins RNA-modifying enzymes and related proteins splicing related factors transcription factors Ubiquitin-related prote

3.5 2.7 2.2 1.1 5.5 2.5 2.7 2.1 3.2 3.6 4.5 10.6 4.6 1.3 4.3 8.9 5.3 30 1.4

function. It is possible that the response of epithelial cells to the challenge varies among qualities and quantities of challenge, locations, and dynamics of exposure, and individuals. Clinical and preclinical investigations of epithelial proteomics should adopt the advanced technologies and follow the development of micro-preparative sample processing, which has been used to analyze single-target phosphoproteins and their relative phospho-stoichiometry.5 Epithelial proteomics will provide powerful information on the relationships between biological molecules and disease mechanisms. Epithelial proteomics strategies and approaches should become more global, multidimensional, and systemic.

Abbreviations 2D-PAGE, two-dimensional gel electrophoresis; LC-MS/MS, liquid chromatography-tandem mass spectrometry; Hsp, heat shock protein.

References (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13)

(14) (15) (16)

Leipziger, J. Am. J. Physiol. Renal. Physiol. 2003, 284, F419-F432. Fink, M. P.; Delude, R. L. Crit. Care Clin. 2005, 21, 177-196. Adler, K. B. J. Organ Dysfunction 2005, 1, 24-25. Zhao, H.; Zhao, X.; Bai, C. X.; Wang, X. D. J. Organ Dysfunction 2005, 1, 32-44. Marko-Varga, G. Am. J. Pharmacogenomics 2005, 5, 113-122. Marko-Varga, G.; Nilsson, J.; Laurell, T. Electrophoresis 2004, 25, 3479-3491. Marko-Varga, G.; Fehniger, T. E. J. Chromatogr. A 2004, 1053, 279-290. Marko-Varga, G.; Fehniger, T. E. J. Proteome Res. 2004, 3, 167178. Malmstro¨m, J.; Malmstro¨m, L.; Marko-Varga, G. A. J. Organ Dysfunction 2005, 1, 83-94. Posadas, E. M.; Davidson, B.; Kohn, E. C. Curr. Opin. Oncol. 2004, 16, 478-484. Wheelock, A. M.; Zhang, L.; Tran, M. U.; Morin, D.; Penn, S.; Buckpitt, A. R.; Plopper, C. G. Am. J. Physiol. Lung Cell Mol. Physiol. 2004, 286, L399-410. Higenbottam, T.; Kuwano, K.; Nemery, B.; Fujita, Y. Br. J. Cancer 2004, 91, S31-37. Jacobs, J. M.; Mottaz, H. M.; Yu, L. R.; Anderson, D. J.; Moore, R. J.; Chen, W. N.; Auberry, K. J.; Strittmatter, E. F.; Monroe, M. E.; Thrall, B. D.; Camp, D. G.; Smith, R. D. J. Proteome Res. 2004, 3, 68-75. Service, R. F. Science 2001, 294, 2074-2077. Hanash, S. M.; Bobek, M. P.; Rickman, D. S.; Williams, T.; Rouillard, J. M.; Kuick, R.; Puravs, E. Proteomics 2002, 2, 69-75. Wulfkuhle, J. D.; McLean, K. C.; Paweletx, C. P.; Sgroi, D. C.; Trock, B. J.; Steeg, P. S.; Petricoin, E. F., III Proteomics 2001, 1, 12051215.

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reviews (17) Wulfkuhle, J. D.; Sgroi, D. C.; Krutzsch, H.; McLean, K.; McGarvey, K.; Knowlton, M.; Chen, S.; Shu, H.; Sahin, A.; Kurek, R.; Wallwiener, D.; Merino, M. J.; Petricoin, E. F., III; Zhao, Y.; Steeg. P. S. Cancer Res. 2002, 62, 6740-6749. (18) Souchelnnytskyi, S. J. Mammary Gland Biol. Neoplasia 2003, 7, 359-71. (19) Lichtenfels, R.; Kellner, R.; Bukur, J.; Beck, J.; Brenner, W.; Ackermann, A.; Seliger, B. Proteomics 2002, 2, 561-570. (20) Young, T. W.; Mei, F. C.; Yang, G.; Thompson-Lanza, J. A.; Liu, J.; Cheng, X. Cancer Res. 2004, 64, 4577-4584. (21) Young, T.; Mei, F.; Liu, J.; Bast, R. C.; Kurosky, A.; Cheng, X. Oncogene 2005, in press. (22) Ostrowski, L. E.; Blackburn, K.; Radde, K. M.; Moyer, M. B.; Schlatzer, D. M.; Moseley, A.; Boucher, R. C. Mol. Cell Proteomics 2002, 1, 451-465. (23) Dosreis, G. A.; Borges, V. M.; Zin, W. A. J. Cell Mol. Med. 2004, 8, 285-293. (24) Chen, J.; Stubbe, J. Nat. Rev. Cancer 2005, 5, 102-112. (25) Luzzi, V.; Holtschlag, V.; Watson, M. A. Am. J. Pathol. 2001, 158, 2005-2010. (26) Kondo, T.; Seike, M.; Mori, Y.; Fujii, K.; Yamada, T.; Hirohashi, S. Proteomics 2003, 3, 1758-1766. (27) Sheehan, K. M.; Calvert, V. S.; Kay, E. W.; Lu, Y.; Fishman, D.; Espina, V.; Aquino, J.; Speer, R.; Araujo, R.; Mills, G. B.; Liotta, L. A.; Petricoin, E. F.; Wulfkuhle, J. D. Mol. Cell Proteomics 2005, 4, 346-355. (28) Shekouh, A. R.; Thompson, C. C.; Prime, W.; Campbell, F.; Hamlett, J.; Herrington, C. S.; Lemoine, N. R.; Crnogorac-Jurcevic, T.; Buechler, M. W.; Friess, H.; Neoptolemos, J. P.; Pennington, S. R.; Costello, E. Proteomics 2003, 3, 1988-2001. (29) Andersen, J. S.; Lam, Y. W.; Leung, A. K. L.; Ong, S. E.; Lyon, C. E.; Lamond, A. I.; Lamond, A. I.; Mann, M. Nature 2005, 433, 7783. (30) Gey, G. O.; Coffman, W. D.; Kubicek, M. T. Cancer Res. 1952, 12, 264. (31) Bonilha, V. L.; Bhattacharya, S. K.; West, K. A.; Sun, J.; Crabb, J. W.; Rayborn, M. E.; Hollyfield, J. G. Mol. Cell Proteomics 2004, 3, 1119-1127. (32) Hong, S.; Gronert, K.; Devchand, P. R.; Moussignac, R. L.; Serhan, C. N. J. Biol. Chem. 2003, 278, 14677-14687. (33) Lee, S. H.; Williams, M. V.; DuBois, R. N.; Blair, I. A. Rapid Commun. Mass Spectrom. 2003, 17, 2168-2176. (34) Chen, W. N.; Yu, L. R.; Strittmatter, E. F.; Thrall, B. D.; Camp, D. G.; Smith, R. D. Proteomics 2003, 3, 1647-1651. (35) Wattiez, R.; Falmagne, P. J. Chromatogr. B 2005, 815, 169-178. (36) Paweletz, C. P.; Trock, B.; Pennanen, M.; Tsangaris, T.; Magnant, C.; Liotta, L. A.; Petricoin, E. F. Dis. Markers 2001, 17, 301-307. (37) Liu, T.; Qian, W. J.; Strittmatter, E. F.; Camp, D. G.; Anderson, G. A.; Thrall, B. D.; Smith, R. D. Anal. Chem. 2004, 76, 5345-5353. (38) Liu, Y., Chen, Q., Zhang, J. T. J. Proteome Res. 2004; 3: 728-735. (39) Pucci-Minafra, I.; Fontana, S.; Cancemi, P.; Alaimo, G.; Minafra, S. Ann. N.Y. Acad. Sci. 2002, 963, 122-139. (40) White, S. L.; Gharbi, S.; Bertani, M. F.; Chan, H. L.; Waterfield, M. D.; Timms, J. F. Br. J. Cancer 2004, 90, 173-181. (41) Ovaa, H.; Kessler, B. M.; Rolen, U.; Galardy, P. J.; Ploegh, H. L.; Masucci, M. G. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 2253-2258. (42) Wilkinson, K. D.; Lee, K. M.; Deshpande, S.; Duerksen-Hughes, P.; Boss, J. M.; Pohl, J. Science 1989, 246, 670-3. (43) Li, C.; Chen, Z.; Xiao, Z.; Wu, X.; Zhan, X.; Zhang, X.; Li, M.; Li, J.; Feng, X.; Liang, S.; Chen, P.; Xie, J. Y. Biochem. Biophys. Res. Commun. 2003, 309, 253-260. (44) Boyer, B.; Valles, A. M.; Edme, N. Biochem. Pharmacol. 2000, 60, 1091-1099. (45) Demir, A. Y.; Demol, H.; Puype, M.; de Goeij, A. F.; Dunselman, G. A.; Herrler, A.; Evers, J. L.; Vandekerckhove, J.; Groothuis, P. G. Proteomics 2004, 4, 2608-2623. (46) Lim, J.; Kim, H.; Kim, J. M.; Kim, J. S.; Jung, H. C.; Kim, K. H. Int. J. Biochem. Cell Biol. 2004, 36, 1624-1634. (47) Marko-Varga, G.; Lindberg, H.; Lofdahl, C. G.; Jonsson, P.; Hansson, L.; Dahlback, M.; Lindquist, E.; Johansson, L.; Foster, M.; Fehniger, T. E. J. Proteome Res. 2005, 4, 1200-1212. (48) Adam, P. J.; Berry, J.; Loader, J. A.; Tyson, K. L.; Craggs, G.; Smith, P.; De Belin, J.; Steers, G.; Pezzella, F.; Sachsenmeir, K. F.; Stamps, A. C.; Herath, A.; Sim, E.; O’Hare, M. J.; Harris, A. L.; Terrett, J. A. Mol. Cancer Res. 2003, 1, 826-835. (49) Badawi, A. F.; Hirvonen, A.; Bell, D. A.; Lang, N. P.; Kadlubar, F. F. Cancer Res. 1995, 55, 5230-5237. (50) Lindquist, S.; Craig, E. A. Annu. Rev. Genet. 1988, 22, 631-677. (51) Fink, A. L. Physiol. Rev. 1999, 79, 425-49.

754

Journal of Proteome Research • Vol. 5, No. 4, 2006

Zhao et al. (52) Brasier, A. R.; Spratt, H.; Wu, Z.; Boldogh, I.; Zhang, Y.; Garofalo, R. P.; Casola, A.; Pashmi, J.; Haag, A.; Luxon, B.; Kurosky, A. J. Virol. 2004, 78, 11461-11476. (53) Lau, A. T.; He, Q. Y.; Chiu, J. F. Biochem. J. 2004, 382, 641-650. (54) Hermeking, H. J. Invest. Dermatol. 2005, 124, ix-x. (55) Hondermarck, H.; Vercoutter-Edouart, A. S.; Revillion, F.; Lemoine, J.; el-Yazidi-Belkoura, I.; Nurcombe, V.; Peyrat, J. P. Proteomics 2001, 1, 1216-1232. (56) Moreira, J. M.; Gromov, P.; Celis, J. E. Mol. Cell Proteomics 2004, 3, 410-419. (57) Bard, M. P.; Hegmans, J. P.; Hemmes, A.; Luider, T. M.; Willemsen, R.; Severijnen, L. A.; van Meerbeeck, J. P.; Burgers, S. A.; Hoogsteden, H. C.; Lambrecht, B. N. Am. J. Respir. Cell Mol. Biol. 2004, 31, 114-121. (58) Trams, E. G.; Lauter, C. J.; Salem, N.; Heine, U. Biochim. Biophys. Acta 1981, 645, 63-70. (59) Barral, A. M.; von Herrath, M. G. Curr. Immunol. Rev. 2005, 1, 1-6. (60) van Balkom, B. W.; Hoffert, J. D.; Chou, C. L.; Knepper, M. A. Am. J. Physiol. Renal. Physiol. 2004, 286, F216-24. (61) Jiang, P. Z.; Gan, M.; Huang, H.; Shen, X. M.; Wang, S.; Yao, K. T. Acta Biochim. Biophys. Sin. 2005, 37, 97-106. (62) Yeung, W. M.; Zong, Y. S.; Chiu, C. T.; Chan, K. H.; Sham, J. S.; Choy, D. T.; Ng, M. H. Int. J. Cancer 1993, 53, 746-750. (63) Gao, Z.; Jin, J.; Yang, J.; Yu, Y. Mutat. Res. 2004, 550, 11-24. (64) Zheng, Y.; Xu, Y.; Ye, B.; Lei, J.; Weinstein, M. H.; O’Leary, M. P.; Richie, J. P.; Mok, S. C.; Liu, B. C. Cancer 2003, 98, 2576-2582. (65) Grubb, R. L.; Calvert, V. S.; Wulkuhle, J. D.; Paweletz, C. P.; Linehan, W. M.; Phillips, J. L.; Chuaqui, R.; Valasco, A.; Gillespie, J.; Emmert-Buck, M.; Liotta, L. A.; Petricoin, E. F. Proteomics 2003, 3, 2142-2146. (66) Wong, Y. F.; Cheung, T. H.; Lo, K. W.; Wang, V. W.; Chan, C. S.; Ng, T. B.; Chung, T. K.; Mok, S. C. Cancer Lett. 2004, 211, 227234. (67) Dhanasekaran, S. M.; Barrette, T. R.; Ghosh, D.; Shah, R.; Varambally, S.; Kurachi, K.; Pienta, K. J.; Rubin, M. A.; Chinnaiyan, A. M. Nature 2001, 412, 822-826. (68) Drew, J. E.; Rucklidge, G. J.; Duncan, G.; Lufty, A.; Farquharson, A. J.; Reid, M. D.; Russell, W. R.; Morrice, P. C.; Arthur, J. R.; Duthie, G. G. Biochem. Biophys. Res. Commun. 2005, 330, 8187. (69) Fehniger, T. E.; Sato-Folatre, J. G.; Malmstrom, J.; Berglund, M.; Lindberg, C.; Brange, C.; Lindberg, H.; Marko-Varga, G. J. Proteome Res. 2004, 3, 307-320. (70) Berman, D. M.; Shih, I. M.; Burke, L. A.; Veenstra, T. D.; Zhao, Y.; Conrads, T. P.; Kwon, S. W.; Hoang, V.; Yu, L. R.; Zhou, M.; Kurman, R. J., Petricoin, E. F.; Liotta, L. A. Proteomics 2004, 4, 812-818. (71) Paweletz, C. P.; Charboneau, L.; Bichsel, V. E.; Simone, N. L.; Chen, T.; Gillespie, J. W.; Emmert-Buck, M. R.; Roth, M. J.; Petricoin, E. F., III; Liotta, L. A. Oncogene 2001, 20, 1981-1989. (72) Liu, X.; Wu, Y.; Zehner, Z. E.; Jackson-Cook, C.; Ware, J. L. Electrophoresis 2003, 24, 3445-3453. (73) Waldburg, N.; Kahne, T.; Reisenauer, A.; Rocken, C.; Welte, T.; Buhling, F. Pathol. Res. Pract. 2004, 200, 147-154. (74) Hendrix, M. J.; Seftor, E. A.; Chu, Y. W.; Trevor, K. T.; Seftor, R. E. Cancer Metastasis Rev. 1996, 15, 507-525. (75) Blanco, D.; Vicent, S.; Elizegi, E.; Pino, I.; Fraga, M. F.; Esteller, M.; Saffiotti, U.; Lecanda, F.; Montuenga, L. M. Lab Invest. 2004, 84, 999-1012. (76) Valkova, N.; Yunis, R.; Mak, S. K.; Kang, K.; Kultz, D. Mol. Cell Proteomics 2005, 4, 1009-1018. (77) Peebles, K. A.; Duncan, M. W.; Ruch, R. J.; Malkinson, A. M. Carcinogenesis 2003, 24, 651-657. (78) Andrew, A. S.; Warren, A. J.; Barchowsky, A.; Temple, K. A.; Klei, L.; Soucy, N. V.; O’Hara, K. A.; Hamilton, J. W. Environ. Health Perspect. 2003, 111, 825-835. (79) Zucchi, I.; Bini, L.; Valaperta, R.; Ginestra, A.; Albani, D.; Susani, L.; Sanchez, J. C.; Liberatori, S.; Magi, B.; Raggiaschi, R.; Hochstrasser, D. F.; Pallini, V.; Vezzoni, P.; Dulbecco, R. Proc. Natl. Acad. Sci. U.S.A. 2001, 98, 5608-5613. (80) Zhu, H.; Snyder, M. Curr. Opin. Chem. Biol. 2001, 5, 40-45. (81) Diaz, J. I.; Cazares, L. H.; Corica, A.; John Semmes, O. Urol. Oncol. 2004, 22, 329-336. (82) Yingling, J. M.; Blanchard, K. L.; Sawyer, J. S. Nat. Rev. Drug Discov. 2004, 3, 1011-1022. (83) Schmidt-Weber, C. B.; Blaser, K. Curr. Opin. Immunol. 2004, 16, 709-716. (84) Kanamoto, T.; Hellman, U.; Heldin, C. H.; Souchelnytskyi, S. EMBO J. 2002, 21, 1219-1230.

reviews

Epithelial Proteomics in Multiple Organs and Tissues (85) Paron, I.; D’Elia, A.; D’Ambrosio, C.; Scaloni, A.; D’Aurizio, F.; Prescott, A.; Damante, G.; Tell, G. Biochem. J. 2004, 378, 929937. (86) Jones, M. B.; Krutzsch, H.; Shu, H.; Zhao, Y.; Liotta, L. A.; Kohn, E. C.; Petricoin, E. F 3rd. Proteomics 2002, 2, 76-84. (87) Sansonetti, P. J. Nat. Rev. Immunol. 2004, 4, 953-964. (88) Williams, M. C. Annu. Rev. Physiol. 2003, 65, 669-695. (89) Trapnell, B. C. Am. J. Physiol. 1993, 264, L199-L212. (90) Sacco, O.; Silvestri, M.; Sabatini, F.; Sale, R.; Defilippi, A. C.; Rossi, G. A. Paediatr. Respir. Rev. 2004, 5, S35-40. (91) Knepper, M. A.; Masilamani, S. Acta Physiol. Scand. 2001, 173, 11-21. (92) Lotze, M. T.; Rees, R. C. Cancer Immunol. Immunother. 2004, 53, 256-261. (93) Morris, A. P.; Estes, M. K. Am. J. Physiol. Gastrointest. Liver Physiol. 2001, 281, G303-G310. (94) Fromm, D. Clin. Invest. Med. 1987, 10, 251-258. (95) Wang, X. D. J. Organ Dysfunction 2005, 1, 1-3. (96) Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., Aebersold, R. Nat. Biotechnol. 1999, 17, 994-999. (97) Fessler, M. B., Malcolm, K. C., Duncan, M. W., Worthen, G. S. J. Biol. Chem. 2002, 277, 31291-31302.

(98) Rohlff, C.; Southan, C. Curr. Opin. Mol. Ther. 2002, 4, 251-258. (99) Krieg, R. C.; Paweletz, C. P.; Liotta, L. A.; Petricoin, E. F. Technol. Cancer Res. Treat 2002, 1, 263-272. (100) Wang, X. D.; Zhao, H.; Andersson, R. J. Proteome Res. 2004, 3, 921-929. (101) Cowherd, S. M.; Espina, V. A.; Petricoin, E. F., 3rd; Liotta, L. A. Clin. Breast Cancer 2004, 5, 385-392. (102) Gershon, D. Nature 2004, 432, 243-249. (103) Crampin, E. J.; Halstead, M.; Hunter, P.; Nielsen, P.; Noble, D.; Smith, N.; Tawhai, M. Exp. Physiol. 2004, 89, 1-26. (104) Fagerquist, C. K.; Miller, W. G.; Harden, L. A.; Bates, A. H.; Vensel, W. H.; Wang, G.; Mandrell, R. E. Anal. Chem. 2005, 77, 48974907. (105) Fessler, M. B.; Malcolm, K. C.; Duncan, M. W.; Worthen, G. S. J. Biol. Chem. 2002, 277, 31291-31302. (106) Lian, Z.; Kluger, Y.; Greenbaum, D. S.; Tuck, D.; Gerstein, M.; Berliner, N.; Weissman, S. M.; Newburger, P. E. Blood 2002, 100, 3209-3220.

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