Purpose A goal of this study was to identify and investigate previously unrecognized components of the remodeling process in the progression to heart failure by comparing protein expression in ischemic failing (F) and nonfailing (NF) human hearts. Experimental design Protein expression differences were investigated using multidimensional protein identification and validated by Western analysis. This approach detected basal lamina (BL) remodeling, and further studies analyzed samples for evidence of structural BL remodeling. A rat model of pressure overload (PO) was studied to determine whether nonischemic stressors also produce BL remodeling and impact cellular adhesion. Results Differential protein expression of collagen IV, laminin α2, and nidogen-1 indicated BL remodeling develops in F versus NF hearts Periodic disruption of cardiac myocyte BL accompanied this process in F, but not NF heart. The rat PO myocardium also developed BL remodeling and compromised myocyte adhesion compared to sham controls. Conclusions and clinical relevance Differential protein expression and evidence of structural and functional BL alterations develop during heart failure. The compromised adhesion associated with this remodeling indicates a high potential for dysfunctional cellular integrity and tethering in failing myocytes. Therapeutically targeting BL remodeling could slow or prevent the progression of heart disease.

Background: ATDC/TRIM29 promotes resistance to ionizing radiation, but the factor(s) that mediate this effect are incompletely understood.Results: ATDC/TRIM29 binds to RNF8, promoting DNA repair and resistance to IR.Conclusion: Following DNA damage, ATDC/TRIM29 is phosphorylated and interacts with RNF8, promoting DNA repair and cell survival.Significance: The interaction between ATDC/TRIM29 and RNF8 is novel and is important for the DNA damage response.Induction of DNA damage by ionizing radiation (IR) and/or cytotoxic chemotherapy is an essential component of cancer therapy. The ataxia telangiectasia group D complementing gene (ATDC, also called TRIM29) is highly expressed in many malignancies. It participates in the DNA damage response downstream of ataxia telangiectasia-mutated (ATM) and p38/MK2 and promotes cell survival after IR. To elucidate the downstream mechanisms of ATDC-induced IR protection, we performed a mass spectrometry screen to identify ATDC binding partners. We identified a direct physical interaction between ATDC and the E3 ubiquitin ligase and DNA damage response protein, RNF8, which is required for ATDC-induced radioresistance. This interaction was refined to the C-terminal portion (amino acids 348-588) of ATDC and the RING domain of RNF8 and was disrupted by mutation of ATDC Ser-550 to alanine. Mutations disrupting this interaction abrogated ATDC-induced radioresistance. The interaction between RNF8 and ATDC, which was increased by IR, also promoted downstream DNA damage responses such as IR-induced gamma-H2AX ubiquitination, 53BP1 phosphorylation, and subsequent resolution of the DNA damage foci. These studies define a novel function for ATDC in the RNF8-mediated DNA damage response and implicate RNF8 binding as a key determinant of the radioprotective function of ATDC.

Raymond L. YungDavid E. Misek, Pascal A. Lescure, Samir Hanash and Ruran Mo, Jun Chen, Yin Han, Cecelia Bueno-Cannizares,http://www.jimmunol.org/content/170/2/895J Immunol€2003; 170:895-904; ;Referenceshttp://www.jimmunol.org/content/170/2/895.full#ref-list-1This article cites 89 articles, 38 of which you can access for free at: Subscriptionshttp://jimmunol.org/subscriptionsInformation about subscribing to The Journal of Immunology is online at: Permissionshttp://www.aai.org/ji/copyright.htmlSubmit copyright permission requests at: Email Alertshttp://jimmunol.org/cgi/alerts/etocReceive free email-alerts when new articles cite this article. Sign up at:

Protein glycosylation is one of the most common posttranslational modifications in mammalian cells. It is involved in many biological pathways and molecular functions and is well suited for proteomics-based disease investigations. Aberrant protein glycosylation may be associated with disease processes. Specific glycoforms of glycoproteins may serve as potential biomarkers for the early detection of disease or as biomarkers for the evaluation of therapeutic efficacy for treatment of cancer, diabetes, and other diseases. Recent technological developments, including lectin affinity chromatography and mass spectrometry, have provided researchers the ability to obtain detailed information concerning protein glycosylation. These in-depth investigations, including profiling and quantifying glycoprotein expression, as well as comprehensive glycan structural analyses may provide important information leading to the development of disease-related biomarkers. This paper describes methodologies for the detection of cancer-related glycoprotein and glycan structural alterations and briefly summarizes several current cancer-related findings.

We have explored the potential of proteomic profiling to contribute to the delineation of the range of expression and subcellular localization of aldehyde dehydrogenases (ALDHs) in lung adenocarcinoma. In-depth quantitative proteomics was applied to 40 lung adenocarcinoma cell lines resulting in the identification of the known members of the ALDH family. Substantial heterogeneity in the level and occurrence of ALDHs in total lysates and on the cell surface and in their release into the culture media was observed based on mass spectrometry counts. A distinct pattern of expression of ALDHs was observed in cells exhibiting epithelial features relative to cells exhibiting mesenchymal features. Strikingly elevated levels of ALDH1A1 were observed in two cell lines. We also report on the occurrence of an immune response to ALDH1A1 in lung cancer.

Advances in breast cancer control will be greatly aided by early detection so as to diagnose and treat breast cancer in its preinvasive state prior to metastasis. For breast cancer, the second leading cause of cancer-related death among women in the United States, early detection does allow for increased treatment options, including surgical resection, with a corresponding better patient response. Unfortunately, however, many patients' tumors are diagnosed following metastasis, thus making it more difficult to successfully treat the malignancy. There are, at present, no existing validated plasma/serum biomarkers for breast cancer. Only a few biomarkers (such as HER-2/neu, estrogen receptor, and progesterone receptor) have utility for diagnosis and prognosis. Thus, there is a great need for new biomarkers for breast cancer. This paper will focus on the identification of new serum protein biomarkers with utility for the early detection of breast cancer.

Sequencing of the human genome has greatly impacted the proteomics-based analysis of disease by providing a framework for understanding the proteome of diseased cells, tissues, and biological fluids. Consequently, there is a growing interest in applying proteomics technologies to define protein pathways involved in various diseases, to identify new biomarkers that correlate with diseases, ideally in their early stages, and to accelerate the development of new therapeutic targets. However, disease-related proteomics applications require that we improve our ability to separate and characterize the components of complex protein mixtures in such a way as to boost both throughput and sensitivity. In response to these demands, the proteomics technologies have been improved markedly over recent years. Today, proteomics, in all its various forms, is proving to be invaluable to our understanding of the biochemistry of health and disease and will likely play a central role in the evolution of personalized medicine. In this special issue, we include reports of novel research findings together with several reviews that highlight advances in key areas. The first two papers of this special issue focus on lung cancer. The first paper, by H. C. Gong et al., addresses the profiling of receptor tyrosine kinase pathway activation and the role of key genetic mutations in human lung tumor cell lines and human lung tumors. The authors defined molecular pathways which may assist in development of targeted lung tumor therapies. Within the second paper, Q. Zhang et al. used proteomic profiling to delineate expression and subcellular localization of multiple forms of aldehyde dehydrogenase in lung adenocarcinoma cell lines. The next two papers focus on pancreatic cancer. The third paper, by R. S. Kwon and D. M. Simeone, reviews the use of protein-based biomarkers for the diagnosis of cystic tumors of the pancreas. The fourth paper, by M. Abulaizi et al., utilizes a three-step proteomic protocol (immunodepletion of abundant serum proteins, followed by fractionation by RP-HPLC and further separation by 2D-PAGE) to discover candidate early detection biomarkers of pancreatic cancer. The next two papers focus on breast cancer, with the fifth paper, by D. E. Misek and E. H. Kim, reviewing the development of protein biomarkers for the early detection of breast cancer. The sixth paper, by J. He et al., addresses LC-MS/MS identification of protein biosignatures in breast tumors, as protein-based markers that correctly classify tumor subtypes and predict therapeutic response would be of great clinical utility in guiding patient treatment. The next two papers are both by M. S. Sabel et al., and focus on melanoma. The seventh paper reviews the use of proteomics for the discovery of new prognostic and predictive biomarkers. The eighth paper explores the clinical utility of serum autoantibodies that were detected in melanoma patients. The investigators profiled serum antibodies against melanoma-associated antigens to identify those that may predict nodal positivity, a widely accepted index of metastatic disease. The ninth paper, by E. H. Kim and D. E. Misek, reviews the use of glycoproteomics to identify cancer biomarkers. The tenth paper, by A. Vivekanandan-Giri et al., utilized glycoproteomics to identify novel urinary glycoprotein biomarkers of chronic kidney disease. The issue concludes with two papers that report on novel approaches and related considerations. The eleventh paper, by I. Kiyokawa et al., describes the development of a new surface coating for urinary collection tubes that minimizes the amount of urine protein adsorption onto the walls of the collection tube. Within the final paper of this special issue, T. Hagiwara et al. examine the utility of a solid-phase hexapeptide ligand library in combination with conventional plasma proteomics modalities for comprehensive profiling of intact plasma proteins. David E. Misek Tadashi Kondo Mark W. Duncan

The proteomic profiles from two distinct ovarian endometrioid tumor-derived cell lines, (MDAH-2774 and TOV-112D) each with different morphological characteristics and genetic mutations, have been studied. Characterization of the differential global protein expression between these two cell lines has important implications for the understanding of the pathogenesis of ovarian endometrioid carcinoma. In this comparative proteomic study, extensive fractionation of peptides generated from whole-cell trypsin digestion was achieved by coupling cIEF in the first-dimensional separation with capillary LC (RP-HPLC) in the second dimensional separation. Online analysis was performed using tandem mass spectra acquired by a linear ion trap mass spectrometer from triplicate runs. A total of 1749 and 1955 proteins with protein probability above 0.95 were identified from MDAH-2774 and TOV-112D after filtering through Peptide Prophet/Protein Prophet software. Differentially expressed proteins were further investigated by ingenuity pathway analysis (IPA) to reveal the association with important biological functions. Canonical pathway analysis using IPA demonstrates that important signaling pathways are highly associated with one of these two cell lines versus the other, such as the PI3K/AKT pathway, which is found to be significantly predominant in MDAH-2774 but not in TOV-112D. Also, protein network analysis using IPA highlights p53 as a central hub relating to other proteins from the connectivity map. These results illustrate the utility of high throughput proteomics methods using large-scale proteome profiling combined with bioinformatics tools to identify differential signaling pathways, thus contributing to the understanding of mechanisms of deregulation in neoplastic cells.

AbstractPurpose: High-frequency microsatellite-instable (MSI-H) tumors account for ∼15% of colorectal cancers. Therapeutic decisions for colorectal cancer are empirically based and currently do not emphasize molecular subclassification despite an increasing collection of gene expression information. Our objective was to identify low molecular weight compounds with preferential activity against MSI colorectal cancers using combined gene expression data sets.Experimental Design: Three expression/query signatures (discovery data set) characterizing MSI-H colorectal cancer were matched with information derived from changes induced in cell lines by 164 compounds using the systems biology tool “Connectivity Map.” A series of sequential filtering and ranking algorithms were used to select the candidate compounds. Compounds were validated using two additional expression/query signatures (validation data set). Cytotoxic, cell cycle, and apoptosis effects of validated compounds were evaluated in a panel of cell lines.Results: Fourteen of the 164 compounds were validated as targeting MSI-H cell lines using the bioinformatics approach; rapamycin, LY-294002, 17-(allylamino)-17-demethoxygeldanamycin, and trichostatin A were the most robust candidate compounds. In vitro results showed that MSI-H cell lines due to hypermethylation of MLH1 are preferentially targeted by rapamycin (18.3 versus 4.4 μmol/L; P = 0.0824) and LY-294002 (15.02 versus 10.37 μmol/L; P = 0.0385) when compared with microsatellite-stable cells. Preferential activity was also observed in MSH2 and MSH6 mutant cells.Conclusion: Our study shows that the phosphatidylinositol 3-kinase-AKT-mammalian target of rapamycin pathway is of special relevance in mismatch repair-deficient colorectal cancer. In addition, we show that amalgamation of gene expression information across studies provides a robust approach for selection of potential therapies corresponding to specific groups of patients.

No validated biomarkers exist for acute graft-versus-host disease (GVHD). We screened plasma with antibody microarrays for 120 proteins in a discovery set of 42 patients who underwent transplantation that revealed 8 potential biomarkers for diagnostic of GVHD. We then measured by enzyme-linked immunosorbent assay (ELISA) the levels of these biomarkers in samples from 424 patients who underwent transplantation randomly divided into training (n = 282) and validation (n = 142) sets. Logistic regression analysis of these 8 proteins determined a composite biomarker panel of 4 proteins (interleukin-2-receptor-alpha, tumor-necrosis-factor-receptor-1, interleukin-8, and hepatocyte growth factor) that optimally discriminated patients with and without GVHD. The area under the receiver operating characteristic curve distinguishing these 2 groups in the training set was 0.91 (95% confidence interval, 0.87-0.94) and 0.86 (95% confidence interval, 0.79-0.92) in the validation set. In patients with GVHD, Cox regression analysis revealed that the biomarker panel predicted survival independently of GVHD severity. A panel of 4 biomarkers can confirm the diagnosis of GVHD in patients at onset of clinical symptoms of GVHD and provide prognostic information independent of GVHD severity.

Ovarian serous carcinomas (OSCs) comprise over half of all ovarian carcinomas and account for the majority of ovarian cancer-related deaths. We used a 2-dimensional liquid-based protein mapping strategy to characterize global protein expression patterns in 19 OSC tumor samples from 15 different patients to facilitate molecular classification of tumor stage. Protein expression profiles were produced, using pI-based separation in the first dimension and hydrophobicity-based separation in the second dimension, over a pH range of 4.0-7.0. Hierarchical clustering was applied to protein maps to indicate the tumor interrelationships. The 19 tumor samples could be classified into two different groups, one group associated with low stage (Stage 1) tumors and the other group associated with high stage (Stages 3/4) tumors. Proteins that were differentially expressed in different groups were selected for identification by LTQ-ESI-MS/MS. Fourteen of the selected proteins were overexpressed in the low stage tumors; 46 of the proteins were overexpressed in the high stage tumors. These proteins are known to play an important role in cellular functions such as glycolysis, protein biosynthesis, and cytoskeleton rearrangement and may serve as markers associated with different stages of OSCs. To further confirm the stage-dependent protein identifications, Lamin A/C and Vimentin expression in ovarian serous carcinomas was assessed by immunohistochemistry using ovarian tumor tissue microarrays for 66 samples.

Ovarian cancer, the second most common gynecological malignancy, accounts for 3% of all cancers among women in the United States, and has a high mortality rate, largely because existing therapies for widespread disease are rarely curative. Ovarian endometrioid adenocarcinoma (OEA) accounts for about 20% of the overall incidence of all ovarian cancer. We have used proteomics profiling to characterize low stage (FIGO stage 1 or 2) versus high stage (FIGO stage 3 or 4) human OEAs. In general, the low stage tumors lacked p53 mutations and had frequent CTNNB1 , PTEN , and/or PIK3CA mutations. The high stage tumors had mutant p53, were usually high grade, and lacked mutations predicted to deregulate Wnt/β‐catenin and PI3K/Pten/Akt signaling. We utilized 2‐D liquid‐based separation/mass mapping techniques to elucidate molecular weight and p I measurements of the differentially expressed intact proteins. We generated 2‐D protein mass maps to facilitate the analysis of protein expression between both the low stage and high stage tumors. These mass maps (over a p I range of 5.6–4.6) revealed that the low stage OEAs demonstrated protein over‐expression at the lower p I ranges (p I 4.8–4.6) in comparison to the high stage tumors, which demonstrated protein over‐expression in the higher p I ranges (p I 5.4–5.2). These data suggest that both low and high stage OEAs have characteristic p I signatures of abundant protein expression probably reflecting, at least in part, the different signaling pathway defects that characterize each group. In this study, the low stage OEAs were distinguishable from high stage tumors based upon the proteomic profiles. Interestingly, when only high‐grade (grade 2 or 3) OEAs were included in the analysis, the tumors still tended to cluster according to stage, suggesting that the altered protein expression was not solely dependent upon tumor cell differentiation. Further, these protein profiles clearly distinguish OEA from other types of ovarian cancer at the protein level.

Background The complexity and heterogeneity of the human plasma proteome have presented significant challenges in the identification of protein changes associated with tumor development. Refined genetically engineered mouse (GEM) models of human cancer have been shown to faithfully recapitulate the molecular, biological, and clinical features of human disease. Here, we sought to exploit the merits of a well-characterized GEM model of pancreatic cancer to determine whether proteomics technologies allow identification of protein changes associated with tumor development and whether such changes are relevant to human pancreatic cancer. Methods and Findings Plasma was sampled from mice at early and advanced stages of tumor development and from matched controls. Using a proteomic approach based on extensive protein fractionation, we confidently identified 1,442 proteins that were distributed across seven orders of magnitude of abundance in plasma. Analysis of proteins chosen on the basis of increased levels in plasma from tumor-bearing mice and corroborating protein or RNA expression in tissue documented concordance in the blood from 30 newly diagnosed patients with pancreatic cancer relative to 30 control specimens. A panel of five proteins selected on the basis of their increased level at an early stage of tumor development in the mouse was tested in a blinded study in 26 humans from the CARET (Carotene and Retinol Efficacy Trial) cohort. The panel discriminated pancreatic cancer cases from matched controls in blood specimens obtained between 7 and 13 mo prior to the development of symptoms and clinical diagnosis of pancreatic cancer. Conclusions Our findings indicate that GEM models of cancer, in combination with in-depth proteomic analysis, provide a useful strategy to identify candidate markers applicable to human cancer with potential utility for early detection.

This chapter focuses on protein sorting in the secretory pathway. From primary and secondary biosynthetic sites in the cytosol and mitochondrial matrix, respectively, proteins and lipids are distributed to more than 30 final destinations in membranes or membrane-bound spaces, where they carry out their programmed function. Molecular sorting is defined, in its most general sense, as the sum of the mechanisms that determine the distribution of a given molecule from its site of synthesis to its site of function in the cell. The final site of residence of a protein in a eukaryotic cell is determined by a combination of various factors, acting in concert: (1) site of synthesis, (2) sorting signals or zip codes, (3) signal recognition or decoding mechanisms, (4) cotranslational or posttranslational mechanisms for translocation across membranes, (5) specific fusion-fission interactions between intracellular vesicular compartments, and (6) restrictions to the lateral mobility in the plane of the bilayer. Improvements in cell fractionation, protein separation, and immune precipitation procedures in the past decade have made them possible. Very little is known about the mechanisms that mediate the localization and concentration of specific proteins and lipids within organelles. Various experimental model systems have become available for their study. The advent of recombinant DNA technology has shortened the time needed for obtaining the primary structure of proteins to a few months.

Pancreatic cancer is resistant to standard surgical and non-selective antimetabolite therapy, with median survival of patients with resectable disease and adjuvant therapy remaining around 20 months and those with unresectable disease at <6 months with the most effective currently available therapy (1, 2). Innovations in genomics and proteomics have led to the identification of numerous potential targets for the development of novel antineoplastic agents and early detection biomarkers. This chapter looks at the history of targeted approaches to drug design, recent developments in the fields of genomics and proteomics, and the potential application of these approaches to pancreatic cancer treatment and early detection. Molecular targeting by pharmaceuticals was made possible in the middle of the last century by the discovery of specific biochemical pathways. Early examples of targeted drugs included propranolol, allopurinol, and cimetidine. Black, Hutchings, and Elion received the Nobel Prize in 1988 for their work on developing these compounds ( 3, 4 ). Identification of similarly specific targets in cancer has noticeably lagged behind, with the exception of antimetabolites. Only recently have targeted therapies such as trastuzumab (anti-HER2 neu antibody effective against breast cancer) and imatinib mesylate (a BCR-ABL tyrosine kinase inhibitor for treatment of chronic myeloid leukemia and gastrointestinal stromal tumors) become available. For pancreatic cancer, bevacizumab (Avastin), a recombinant humanized antivascular endothelial growth factor (VEGF) monoclonal antibody, showed promising results in phase II trials ( 5 ), but was subsequently shown to provide no survival benefit ( 6 ). The push to identify specific molecular targets for the rational design of antineoplastics (in particular cancer cell signaling molecules and molecules that can affect the cancer cell microenvironment) has led to rapid development of techniques in genomics and proteomics. These techniques hold promise in identifying novel and effective targets for the treatment of pancreatic cancer.