High-throughput proteomics of breast carcinoma cells: a focus on FTICR-MS

Discovery of better biomarkers for diagnosis, prognosis and therapy-response prediction is the most critical task of a scientific quest aimed at developing novel, tailormade therapies for patients with cancer. Consequently, a proteome-wide analysis, in addition to genomic studies, is an absolute requirement for a complete functional understanding of tumor biology. Ultra-sensitive, high-performance Fourier-transform ion-cyclotron resonance (FTICR) mass spectrometry (MS) currently holds an important role in fulfilling the demands of biomarker discovery. In this review, we describe the applicability of FTICR-MS for breast cancer proteomics, particularly for the analysis of complex protein mixtures obtained from a limited number of cells typically available from clinical specimens.     

A European focus on proteomics

A report on the First International Symposium of the Austrian Proteomics Platform, Seefeld, Austria, 26-29 January 2004.     

High-throughput proteomics: a flexible and efficient pipeline for protein production

Many studies that aim to characterize the proteome require the production of pure protein in a high-throughput format. We have developed a system for high-throughput subcloning, protein expression and purification that is simple, fast, and inexpensive. We utilized ligation-independent cloning with a custom-designed vector and developed an expression screen to test multiple parameters for optimal protein production in E. coli. A 96-well format purification protocol that produced microgram quantities of pure protein was also developed.     

Targeted proteomics in Alzheimer's disease: focus on amyloid-beta

Diagnosis and monitoring of sporadic Alzheimer's disease (AD) have long depended on clinical examination of individuals with end-stage disease. However, upcoming anti-AD therapies are optimally initiated when individuals show very mild signs of neurodegeneration. There is a developing consensus for cerebrospinal fluid amyloid-beta (Abeta) as a core biomarker for the mild cognitive impairment stage of AD. Abeta is directly involved in the pathogenesis of AD or tightly correlated with other primary pathogenic factors. It is produced from amyloid precursor protein (APP) by proteolytic processing that depends on the beta-site APP-cleaving enzyme 1 and the gamma-secretase complex, and is degraded by a broad range of proteases. This review summarizes targeted proteomic studies of Abeta in biological fluids and identifies clinically useful markers of disrupted Abeta homeostasis in AD. The next 5 years will see a range of novel assays developed on the basis of these results. From a longer perspective, establishment of the most effective combinations of different biomarkers and other diagnostic modalities may be foreseen.     

High-throughput proteomic analysis of human infiltrating ductal carcinoma of the breast

Large-scale proteomics will play a critical role in the rapid display, identification and validation of new protein targets, and elucidation of the underlying molecular events that are associated with disease development, progression and severity. However, because the proteome of most organisms are significantly more complex than the genome, the comprehensive analysis of protein expression changes will require an analytical effort beyond the capacity of standard laboratory equipment. We describe the first high-throughput proteomic analysis of human breast infiltrating ductal carcinoma (IDCA) using OCT (optimal cutting temperature) embedded biopsies, two-dimensional difference gel electrophoresis (2-D DIGE) technology and a fully automated spot handling workstation. Total proteins from four breast IDCAs (Stage I, IIA, IIB and IIIA) were individually compared to protein from non-neoplastic tissue obtained from a female donor with no personal or family history of breast cancer. We detected differences in protein abundance that ranged from 14.8% in stage I IDCA versus normal, to 30.6% in stage IIB IDCA versus normal. A total of 524 proteins that showed > or = three-fold difference in abundance between IDCA and normal tissue were picked, processed and identified by mass spectrometry. Out of the proteins picked, approximately 80% were unambiguously assigned identities by matrix-assisted laser desorbtion/ionization-time of flight mass spectrometry or liquid chromatography-tandem mass spectrometry in the first pass. Bioinformatics tools were also used to mine databases to determine if the identified proteins are involved in important pathways and/or interact with other proteins. Gelsolin, vinculin, lumican, alpha-1-antitrypsin, heat shock protein-60, cytokeratin-18, transferrin, enolase-1 and beta-actin, showed differential abundance between IDCA and normal tissue, but the trend was not consistent in all samples. Out of the proteins with database hits, only heat shock protein-70 (more abundant) and peroxiredoxin-2 (less abundant) displayed the same trend in all the IDCAs examined. This preliminary study demonstrates quantitative and qualitative differences in protein abundance between breast IDCAs and reveals 2-D DIGE portraits that may be a reflection of the histological and pathological status of breast IDCA.     

High-throughput proteomics processing of proteins in polyacrylamide in a multiwell format

Processing multiple protein samples from polyacrylamide at significant sensitivity represents a major chokepoint for raising the success rate in high-volume protein identification projects. A multiwell filterplate method for processing proteins in polyacrylamide was optimized for sensitivity using a protein standard. The results demonstrate this process to be a reliable and reproducible method over a range of gel loadings and suitable for the identification of proteins near the threshold of silver stain. This high-throughput manual method requires a minimum of specialized equipment, and can be performed disconnected from a proteomics infrastructure for the preparation of mass spectrometry-ready samples.     

High-throughput screening of structural proteomics targets using NMR

We applied a high-throughput strategy for the screening of targets for structural proteomics of Xanthomonas axonopodis pv citri. This strategy is based on the rapid (1)H-(15)N HSQC NMR analysis of bacterial lysates containing selectively (15)N-labelled heterologous proteins. Our analysis permitted us to classify the 19 soluble candidates in terms of 'foldedness', that is, the extent to which they present a well-folded solution structure, as reflected by the quality of their NMR spectra. This classification allowed us to define a priority list to be used as a guide to select protein candidates for further structural studies.     

Comparative proteomics between natural Microcystis isolates with a focus on microcystin synthesis

ABSTRACT: BACKGROUND: Microcystis aeruginosa is a species of cyanobacteria commonly found in a number of countries and frequently related to animal poisoning episodes due to its capacity to produce the cyanotoxin known as microcystin. Despite vast literature on microcystin structures and their deleterious effects, little is known about its synthesis by cyanobacteria. Therefore, this study used proteomic tools to compare two M. aeruginosa strains, contrasting them for microcystin production. RESULTS: 2-DE gels were performed and 30 differential protein spots were chosen. Among them, 11 protein spots were unique in the toxin producing strain and 8 in the non-toxin producing strain, and 14 protein spots were shown on both 2-DE gels but expressed differently in intensity. Around 57% of the tandem mass spectrometry identified proteins were related to energy metabolism, with these proteins being up-regulated in the toxin producing strain. CONCLUSIONS: These data suggest that the presence of higher quantities of metabolic enzymes could be related to microcystin metabolism in comparison to the non-toxin producing strain. Moreover, it was suggested that the production of microcystin could also be related to other proteins than those directly involved in its production, such as the enzymes involved in the Calvin cycle and glycolysis.     

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

Introduction: Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification.

Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references.

Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.     

Chemotherapy of breast cancer: focus on paclitaxel

Paclitaxel is among the most effective agents in the treatment of breast cancer. Both as a single agent and in combinations, paclitaxel is effective as first-line therapy and as a salvage therapy in patients with locally advanced or metastatic disease. Paclitaxel also demonstrated efficacy in patients who received prior anthracyclin therapy and those with anthracyclin-resistant disease. In the adjuvant setting, data from randomized study have supported the sequential use of paclitaxel after therapy with doxorubicin / cyclophosphamide for patients with node-positive disease. The drug may be used in combination with other chemotherapeutical agents and immune stymulatory agents. Therapy on weekly and every-three-week schedules has been effective.     

High-throughput proteomics: protein expression and purification in the postgenomic world.

Proteomics has become a major focus as researchers attempt to understand the vast amount of genomic information. Protein complexity makes identifying and understanding gene function inherently difficult. The challenge of studying proteins in a global way is driving the development of new technologies for systematic and comprehensive analysis of protein structure and function. Protein expression and purification are key processes in these studies, but have typically only been applied on a case-by-case basis to proteins of interest. Researchers are addressing the challenge of parallel expression and purification of large numbers of gene products through the principles of high-throughput screening technologies commonly used in pharmaceutical development. Some of the issues relevant to these approaches are discussed here.     

Evaluation of metabolic labeling for comparative proteomics in breast cancer cells

Protein expression patterns in the cytosol of MCF-7 cells resistant to adriamycin and to adriamycin/verapamil were compared to that of the parental MCF-7 cell line and to each other using metabolic labeling and two-dimensional gel electrophoresis. Growing the parental MCF-7 cell line in 13C6-arginine- and 13C6-lysine-enriched medium resulted in C-terminal labeling of all tryptic peptides. The culture media was optimized for the incorporation of these labeled amino acids under conditions that also supported cell growth. Protein abundances were found to be distinctive in MCF-7 cells resistant to adriamycin and those selected for resistance to both adriamycin and verapamil.     

High-throughput RNAi screening in cultured cells: a user's guide

RNA interference has re-energized the field of functional genomics by enabling genome-scale loss-of-function screens in cultured cells. Looking back on the lessons that have been learned from the first wave of technology developments and applications in this exciting field, we provide both a user's guide for newcomers to the field and a detailed examination of some more complex issues, particularly concerning optimization and quality control, for more advanced users. From a discussion of cell lines, screening paradigms, reagent types and read-out methodologies, we explore in particular the complexities of designing optimal controls and normalization strategies for these challenging but extremely powerful studies.     

Plasma membrane proteomics of human embryonic stem cells and human embryonal carcinoma cells

Human embryonic stem cells (hESCs) are of immense interest in regenerative medicine as they can self-renew indefinitely and can give rise to any adult cell type. Human embryonal carcinoma cells (hECCs) are the malignant counterparts of hESCs found in testis tumors. hESCs that have acquired chromosomal abnormalities in culture are essentially indistinguishable from hECC. Direct comparison of karyotypically normal hESCs with hECCs could lead to understanding differences between their mechanisms of growth control and contribute to implementing safe therapeutic use of stem cells without the development of germ cell cancer. While several comparisons of hECCs and hESCs have been reported, their cell surface proteomes are largely unknown, partly because plasma membrane proteomics is still a major challenge. Here, we present a strategy for the identification of plasma membrane proteins that has been optimized for application to the relatively small numbers of stem cells normally available, and that does not require tedious cell fractionation. The method led to the identification of 237 and 219 specific plasma membrane proteins in the hESC line HUES-7 and the hECC line NT2/D1, respectively. In addition to known stemness-associated cell surface markers like ALP, CD9, and CTNNB, a large number of receptors, transporters, signal transducers, and cell-cell adhesion proteins were identified. Our study revealed that several Hedgehog and Wnt pathway members are differentially expressed in hESCs and hECCs including NPC1, FZD2, FZD6, FZD7, LRP6, and SEMA4D, which play a pivotal role in stem cell self-renewal and cancer growth. Various proteins encoded on chromosome 12p, duplicated in testicular cancer, were uniquely identified in hECCs. These included GAPDH, LDHB, YARS2, CLSTN3, CSDA, LRP6, NDUFA9, and NOL1, which are known to be upregulated in testicular cancer. Distinct HLA molecules were revealed on the surface of hESCs and hECCs, despite their low abundance. Results were compared with genomic and proteomic data sets reported previously for mouse ESCs, hECCs, and germ cell tumors. Our data provides a surface signature for HUES-7 and NT2/D1 cells and distinguishes normal hESCs from hECCs, helping explain their 'benign' versus 'malignant' nature.     

High-throughput screening of cellular redox sensors using modern redox proteomics approaches

Cancer cells are characterized by higher levels of intracellular reactive oxygen species (ROS) due to metabolic aberrations. ROS are widely accepted as second messengers triggering pivotal signaling pathways involved in the process of cell metabolism, cell cycle, apoptosis, and autophagy. However, the underlying cellular mechanisms remain largely unknown. Recently, accumulating evidence has demonstrated that ROS initiate redox signaling through direct oxidative modification of the cysteines of key redox-sensitive proteins (termed redox sensors). Uncovering the functional changes underlying redox regulation of redox sensors is urgently required, and the role of different redox sensors in distinct disease states still remains to be identified. To assist this, redox proteomics has been developed for the high-throughput screening of redox sensors, which will benefit the development of novel therapeutic strategies for cancer treatment. Highlighted here are recent advances in redox proteomics approaches and their applications in identifying redox sensors involved in tumor development.