Astrid Slany

Cell characterization by proteome profiling applied to primary hepatocytes and hepatocyte cell lines Hep-G2 and Hep-3B.

Hepatocytes are known to express a large number of characteristic proteins. Transformed and cultured hepatocytes only partially maintain functional cell differentiation characteristics, which can be assessed by proteome profiling. Here, we applied 2D-PAGE analysis in addition to shotgun proteomics to assess the functional cell state of primary human hepatocytes (PHH), HepG2 and Hep3B cells. Out of a total of 1995 proteins identified in the cytoplasm of these cells, we filtered 107 proteins which are characteristic for hepatocytes. A total of 104 of those were identified in primary human hepatocytes, 20 in HepG2, and only 6 in Hep3B. Forty-six out of 72 proteins identified in the secretome of PHH, 55 out of 139 in HepG2, and only 24 out of 72 in Hep3B were plasma proteins characteristic for hepatocytes. Beside other biomarker candidates presently identified, 11 proteins of the HepG2 secretome have been described previously as biomarkers for hepatocellular carcinoma. Because of indications that epithelial to mesenchymal transition (EMT) may have occurred in the cultured hepatoma cells, we included the analysis of fibroblasts representative for mesenchymal cells. Hep3B, but not HepG2, secreted five proteins including follistatin-related protein 1 which are characteristic for mesenchymal cells and may be marker proteins for EMT. Our data demonstrate that HepG2 show more features characteristic for hepatocytes than Hep3B, while Hep3B express more mesenchymal proteins indicative for EMT. Proteome profiling thus proved to enable comprehensive assessment of functional cell states and cell differentiation states of cultured hepatocytes and enabled the identification of numerous biomarkers for hepatocellular carcinoma and EMT.

Proteome maps of the main human peripheral blood constituents.

Clinical proteome analysis will almost inevitably be confronted with blood constituents. Purified plasma, serum, cell or tissue samples may easily be contaminated with some other constituents, affecting the final proteome analysis result. To recognize proteins which are potentially indicative for the presence of major blood constituents, we purified T cells, monocytes, neutrophils, erythrocytes, platelets and plasma and performed comparative proteome profiling employing 2D-PAGE in addition to shotgun proteomics. By mass analysis, 594 different proteins were identified in the 2D gels. Six of the 594 proteins displayed a highly specific expression pattern. A total of 1774 proteins were identified by shotgun proteomics, including 50 proteins with highly specific expression patterns. Indeed, proteins specific for each of the constituents were successfully identified. All protein lists including mass spectrometry details and expression specificity are freely available via the PRIDE database and the CPL/MUW database. The present protein maps of each of the constituents may serve as references for comparative analyses and will aid the interpretation of proteome profiles of clinical samples.

Entering a New Era of Rational Biomarker Discovery for Early Detection of Melanoma Metastases: Secretome Analysis of Associated Stroma Cells

Metastasis in melanoma is associated with poor prognosis. Early detection may thus substantially improve patient survival. Here we present a novel biomarker discovery strategy based on proteome profiling and secretome analysis of primary cells. Tumor associated stroma cells secrete proteins that may act as powerful tumor promoters. This cell cooperativity is reversible and may thus be directly accessible to therapeutic intervention. The onset of these characteristic events seems to precede tumor progression. Thus, proteins specifically secreted by these cells may serve as early disease biomarkers. Due to the leaky nature of newly formed blood vessels and the increased hydrostatic pressure within tumors, secreted proteins are most plausibly shed into the blood. Our analysis strategy is based on three different model systems, including established cultured cell lines, animal model systems, and clinical human samples. The feasibility is demonstrated with secretome and proteome profiles generated from normal human skin fibroblasts in comparison to melanoma-associated fibroblasts isolated from mouse xenografts and fibroblasts from bone marrow of multiple myeloma patients. Further mutual comparisons were enabled including proteome profiles of melanocytes and M24met melanoma cells. All shotgun proteomics data are accessible via the PRIDE database. Among others, the candidate biomarkers GPX5, secreted by melanoma cells, in addition to periostin and stanniocalcin-1, which are expressed by melanoma-associated fibroblasts were identified. In conclusion, this is a novel strategy to identify diagnostic marker proteins aiding early detection of metastatic melanoma and to improve our understanding of pathomechanisms involving the microenvironment to enable the design of novel therapeutic strategies.

Cytoplasmic proteome and secretome profiles of differently stimulated human dendritic cells.

Dendritic cells (DCs), the most potent and specialized antigen-presenting cells, play a key role in the regulation of the adaptive immunity. Immature DCs were generated by in vitro culturing of peripheral blood monocytes and functionally activated with the classical pathogen-associated molecular pattern lipopolysaccharide (LPS). Alternative activation resulting in Th-2 polarization was induced with lipid oxidation products derived from 1-palmitoyl-2-arachidoyl-sn-glycerol-3-phosphorylcholin (OxPAPC). Tolerogenic cells were obtained by treating DCs with human rhinovirus (HRV). The aim of this study was the identification of proteome profiles related to the functionally different dendritic cell phenotypes. Cytoplasmic proteins were analyzed by shotgun proteomics resulting in the identification of 1690 proteins. While mature and alternatively activated DCs displayed highly distinct protein expression profiles, HRV-treated DCs showed minor proteome alterations. As DCs exert many specific functions via secretion, we investigated the secretomes by a combination of 2D-PAGE and shotgun proteomics. We successfully identified a broad variety of cytokines (e.g., GM-CSF, TNF-alpha, interleukin-1beta, 6, 12 beta, 28B and 29), chemokines (e.g., CCL3, 5, 8, 17, 18, 19, 24, CXCL1, 2, 9 and 10) and growth factors (growth/differentiation factor 8, C-type lectin domain family 11 member A). The relative composition of secretome profiles, although comprising much less proteins, was found to be much more affected by functional alteration of cells than the cytoplasmic protein composition. In conclusion, we demonstrate that functional distinct subsets of DCs display distinct proteome profiles which comprise biomarker candidates. These proteins may prove useful for the interpretation of complex clinical proteomics data.

Proteome signatures of inflammatory activated primary human peripheral blood mononuclear cells

Proteome profiling is the method of choice to identify marker proteins whose expression may be characteristic for certain diseases. The formation of such marker proteins results from disease-related pathophysiologic processes. In healthy individuals, peripheral blood mononuclear cells (PBMCs) circulate in a quiescent cell state monitoring potential immune-relevant events, but have the competence to respond quickly and efficiently in an inflammatory manner to any invasion of potential pathogens. Activation of these cells is most plausibly accompanied by characteristic proteome alterations. Therefore we investigated untreated and inflammatory activated primary human PBMCs by proteome profiling using a ‘top down’ 2D-PAGE approach in addition to a ‘bottom up’ LC–MS/MS-based shotgun approach. Furthermore, we purified primary human T-cells and monocytes and activated them separately. Comparative analysis allowed us to characterize a robust proteome signature including NAMPT and PAI2 which indicates the activation of PBMCs. The T-cell specific inflammation signature included IRF-4, GBP1and the previously uncharacterized translation product of GBP5; the corresponding monocyte signature included PDCD5, IL1RN and IL1B. The involvement of inflammatory activated PBMCs in certain diseases as well as the responsiveness of these cells to anti-inflammatory drugs may be evaluated by quantification of these marker proteins. This article is part of a Special Issue entitled: Integrated omics.

Introducing a new parameter for quality control of proteome profiles : Consideration of commonly expressed proteins

Interpretation of proteome profiling experiments largely relies on comparative analyses. False‐positive identifications may cause fatal misinterpretation of data. On the other hand, proteome analysis may also suffer from false negatives, when proteins that are actually present are not detected. This circumstance may be as fatal as false‐positive identifications and was hardly considered until now. Appropriate positive controls would facilitate quality assessment of proteome profiling experiments. Based on cell biology knowledge, our aim was to generate a list of commonly expressed proteins, which may serve as positive control. Following a pragmatic experimental strategy, we compared the cytoplasmic fractions of four largely differing kinds of cells, which were human DCs, endothelial cells, fibroblasts and keratinocytes. Proteome profiling was performed by 2D‐PAGE in addition to shotgun analysis. By shotgun analysis, 665 proteins were identified, which occurred in each of the four cells types; 360 proteins of those were also detectable in the corresponding 2‐D gels. We consider these proteins as common proteins. All shotgun analysis data, including mass fragmentation spectra of the corresponding peptides, are accessible via the proteomics identification database (http://www.ebi.ac.uk/pride). As expected, most of the common proteins could be clearly assigned to at least one of the following functional categories: chaperones, cytoskeleton, energy metabolism, redox regulation, nucleic acid processing, protein turnover, membrane transport, protein synthesis and signaling. We suggest that the present data may prove helpful for data assessment, quality control and interpretation of a large variety of experiments based on proteome profiling.

Comprehensive Assessment of Proteins Regulated by Dexamethasone Reveals Novel Effects in Primary Human Peripheral Blood Mononuclear Cells

Inflammation is a physiological process involved in many diseases. Monitoring proteins involved in regulatory effects may help to improve our understanding of inflammation. We have analyzed proteome alterations induced in peripheral blood mononuclear cells (PBMCs) upon inflammatory activation in great detail using high-resolution mass spectrometry. Moreover, the activated cells were treated with dexamethasone to investigate their response to this antiphlogistic drug. From a total of 6886 identified proteins, 469 proteins were significantly regulated upon inflammatory activation. Data are available via ProteomeXchange with identifiers PXD001415-23. Most of these proteins were counter-regulated by dexamethasone, with some exceptions concerning members of the interferon-induced protein family. To confirm some of these results, we performed targeted MRM analyses of selected peptides. The inflammation-induced upregulation of proteins such as IL-1β, IL-6, CXCL2, and GROα was confirmed, however, with strong quantitative interindividual differences. Furthermore, the inability of dexamethasone to downregulate inflammation-induced proteins such as PTX3 and TSG6 was clearly demonstrated. In conclusion, the relation of cell function as well as drug-induced modulation thereof was successfully mapped to proteomes, suggesting targeted analysis as a novel and powerful drug evaluation method. Although most consequences of dexamethasone were found to be compatible with the expected mode of action, some unexpected but significant observations may be related to adverse effects.

Extracellular Matrix Remodeling by Bone Marrow Fibroblast-like Cells Correlates with Disease Progression in Multiple Myeloma

The pathogenesis of multiple myeloma (MM) is regarded as a multistep process, in which an asymptomatic stage of monoclonal gammopathy of undetermined significance (MGUS) precedes virtually all cases of MM. Molecular events characteristic for the transition from MGUS to MM are still poorly defined. We hypothesized that fibroblast-like cells in the tumor microenvironment are critically involved in the pathogenesis of MM. Therefore, we performed a comparative proteome profiling study, analyzing primary human fibroblast-like cells isolated from the bone marrow of MM, of MGUS, as well as of non-neoplastic control patients. Thereby, a group of extracellular matrix (ECM) proteins, ECM receptors, and ECM-modulating enzymes turned out to be progressively up-regulated in MGUS and MM. These proteins include laminin α4, lysyl-hydroxylase 2, prolyl 4-hydroxylase 1, nidogen-2, integrin α5β5, c-type mannose receptor 2, PAI-1, basigin, and MMP-2, in addition to PDGF-receptor β and the growth factor periostin, which are likewise involved in ECM activities. Our results indicate that ECM remodeling by fibroblast-like cells may take place already at the level of MGUS and may become even more pronounced in MM. The identified proteins which indicate the stepwise progression from MGUS to MM may offer new tools for therapeutic strategies.

Introducing the CPL/MUW proteome database: interpretation of human liver and liver cancer proteome profiles by referring to isolated primary cells.

Interpretation of proteome data with a focus on biomarker discovery largely relies on comparative proteome analyses. Here, we introduce a database‐assisted interpretation strategy based on proteome profiles of primary cells. Both 2‐D‐PAGE and shotgun proteomics are applied. We obtain high data concordance with these two different techniques. When applying mass analysis of tryptic spot digests from 2‐D gels of cytoplasmic fractions, we typically identify several hundred proteins. Using the same protein fractions, we usually identify more than thousand proteins by shotgun proteomics. The data consistency obtained when comparing these independent data sets exceeds 99% of the proteins identified in the 2‐D gels. Many characteristic differences in protein expression of different cells can thus be independently confirmed. Our self‐designed SQL database (CPL/MUW – database of the Clinical Proteomics Laboratories at the Medical University of Vienna accessible via www.meduniwien.ac.at/proteomics/database) facilitates (i) quality management of protein identification data, which are based on MS, (ii) the detection of cell type‐specific proteins and (iii) of molecular signatures of specific functional cell states. Here, we demonstrate, how the interpretation of proteome profiles obtained from human liver tissue and hepatocellular carcinoma tissue is assisted by the Clinical Proteomics Laboratories at the Medical University of Vienna‐database. Therefore, we suggest that the use of reference experiments supported by a tailored database may substantially facilitate data interpretation of proteome profiling experiments.

Proteome profiling of breast cancer biopsies reveals a wound healing signature of cancer-associated fibroblasts.

Breast cancer is still the most common type of cancer in women; an important role in carcinogenesis is actually attributed to cancer-associated fibroblasts. In this study, we investigated whether it is possible to assess the functional state of cancer-associated fibroblasts through tumor tissue proteome profiling. Tissue proteomics was performed on tumor-central, tumor-near, and tumor-distant biopsy sections from breast adenocarcinoma patients, which allowed us to identify 2074 proteins. Data were interpreted referring to reference proteome profiles generated from primary human mammary fibroblasts comprising 4095 proteins. These cells were analyzed in quiescent cell state as well as after in vitro treatment with TGFβ or IL-1β, stimulating wound healing or inflammatory processes, respectively. Representative for cancer cells, we investigated the mammary carcinoma cell line ZR-75-1, identifying 5212 proteins. All mass analysis data have been made fully accessible via ProteomeXchange, DOI PXD001311 and PXD001323-8. Comparison of tissue proteomics data with all of those reference profiles revealed predominance of cancer cell-derived proteins within the tumor and fibroblast-derived proteins in the tumor-distant tissue sections. Remarkably, proteins characteristic for acute inflammation were hardly identified in the tissue samples. In contrast, several proteins found by us to be induced by TGFβ in mammary fibroblasts, including fibulin-5, SLC2A1, and MUC18, were positively identified in all tissue samples, with relatively higher abundance in tumor neighboring tissue sections. These findings indicate a predominance of cancer-associated fibroblasts with wound healing activities localized around tumors.