Identification of androgen-coregulated protein networks from the microsomes of human prostate cancer cells

Review of the Real and Sometimes Hidden Costs in Proteomics Experimental Workflows

A typical proteomics workflow covers all the steps from growing or collecting the cells/tissues/organism, protein extraction, digestion and cleanup, mass spectrometric analysis, and, finally, extensive bioinformatics to derive biological insight from the data. The details of the procedures employed for this can vary widely by laboratory and by sample type: e.g., hard tissues or cells with walls require much more mechanical disruption to extract proteins than do soft tissues, biological fluids, or wall-less cells. Everything then converges on the mass spectrometer, where there are further choices to be made about how to do the analysis. There is one commonality, however, virtually every group around the world now uses liquid chromatography on-line coupled to tandem mass spectrometry, which means that significant amounts of instrument time are dedicated to every sample. There are many other reviews or methods papers, including in this volume, that cover the details of the various procedures involved in proteomic analyses of all types of samples. Our focus here will be on the cost considerations for such analyses, including considerations to ensure that useful data can be obtained the first time a sample is analyzed. Some of these costs are often overlooked, particularly for those groups who operate their own mass spectrometer(s) and do not have to go to a fee-for-service facility to have something analyzed. The chapter presents several challenges and key suggestions in proving hypotheses in proteomics experimental workflow in different biological systems with specific regard to the costs involved, both real and hidden. The detailed methodology for cost-based studies reported in this chapter can help researchers to set up their laboratory with appropriate equipment as well as to identify potential collaborations based on their analytical instrumentation.

Research Resource: Androgen Receptor Activity Is Regulated Through the Mobilization of Cell Surface Receptor Networks

The aberrant expression of androgen receptor (AR)-dependent transcriptional programs is a defining pathology of the development and progression of prostate cancers. Transcriptional cofactors that bind AR are critical determinants of prostate tumorigenesis. To gain a deeper understanding of the proteins linked to AR-dependent gene transcription, we performed a DNA-affinity chromatography-based proteomic screen designed to identify proteins involved in AR-mediated gene transcription in prostate tumor cells. Functional experiments validated the coregulator roles of known AR-binding proteins in AR-mediated transcription in prostate tumor cells. More importantly, novel coregulatory functions were detected in components of well-established cell surface receptor-dependent signal transduction pathways. Further experimentation demonstrated that components of the TNF, TGF-β, IL receptor, and epidermal growth factor signaling pathways modulated AR-dependent gene transcription and androgen-dependent proliferation in prostate tumor cells. Collectively, our proteomic dataset demonstrates that the cell surface receptor- and AR-dependent pathways are highly integrated, and provides a molecular framework for understanding how disparate signal-transduction pathways can influence AR-dependent transcriptional programs linked to the development and progression of human prostate cancers.

Androgen receptor and chemokine receptors 4 and 7 form a signaling axis to regulate CXCL12-dependent cellular motility

Background

Identifying cellular signaling pathways that become corrupted in the presence of androgens that increase the metastatic potential of organ-confined tumor cells is critical to devising strategies capable of attenuating the metastatic progression of hormone-naïve, organ-confined tumors. In localized prostate cancers, gene fusions that place ETS-family transcription factors under the control of androgens drive gene expression programs that increase the invasiveness of organ-confined tumor cells. C-X-C chemokine receptor type 4 (CXCR4) is a downstream target of ERG, whose upregulation in prostate-tumor cells contributes to their migration from the prostate gland. Recent evidence suggests that CXCR4-mediated proliferation and metastasis of tumor cells is regulated by CXCR7 through its scavenging of chemokine CXCL12. However, the role of androgens in regulating CXCR4-mediated motility with respect to CXCR7 function in prostate-cancer cells remains unclear.

Methods

Immunocytochemistry, western blot, and affinity-purification analyses were used to study how androgens influenced the expression, subcellular localization, and function of CXCR7, CXCR4, and androgen receptor (AR) in LNCaP prostate-tumor cells. Moreover, luciferase assays and quantitative polymerase chain reaction (qPCR) were used to study how chemokines CXCL11 and CXCL12 regulate androgen-regulated genes (ARGs) in LNCaP prostate-tumor cells. Lastly, cell motility assays were carried out to determine how androgens influenced CXCR4-dependent motility through CXCL12.

Results

Here we show that, in the LNCaP prostate-tumor cell line, androgens coordinate the expression of CXCR4 and CXCR7, thereby promoting CXCL12/CXCR4-mediated cell motility. RNA interference experiments revealed functional interactions between AR and CXCR7 in these cells. Co-localization and affinity-purification experiments support a physical interaction between AR and CXCR7 in LNCaP cells. Unexpectedly, CXCR7 resided in the nuclear compartment and modulated AR-mediated transcription. Moreover, androgen-mediated cell motility correlated positively with the co-localization of CXCR4 and CXCR7 receptors, suggesting that cell migration may be linked to functional CXCR4/CXCR7 heterodimers. Lastly, CXCL12-mediated cell motility was CXCR7-dependent, with CXCR7 expression required for optimal expression of CXCR4 protein.

Conclusions

Overall, our results suggest that inhibition of CXCR7 function might decrease the metastatic potential of organ-confined prostate cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1201-5) contains supplementary material, which is available to authorized users.

Androgen-sensitive microsomal signaling networks coupled to the proliferation and differentiation of human prostate cancer cells

Increasing evidence suggests that the disruption of androgen-mediated cellular processes, such as cell proliferation and cell differentiation, contributes to the development of early-stage androgen-dependent prostate cancers. Large-scale mRNA profiling experiments have paved the way in identifying androgen-regulated gene networks that control the proliferation, survival, and differentiation of prostate cancer cells. Despite these extensive research efforts, it remains to be determined whether all androgen-mediated mRNA changes faithfully translate into changes in protein abundance that influence prostate tumorigenesis. Here, we report on a mass spectrometry-based quantitative proteomics analysis that identified known androgen signaling pathways and also novel, androgen-sensitive microsome-associated proteins and protein networks that had not been discovered by gene network studies in human LNCaP prostate cancer cells. Androgen-sensitive microsome-associated proteins encoded components of the insulin growth factor-1 (IGF-1), phosphoinositide 3-kinase (PI3K)/AKT, and extracellular signal-regulated kinase (ERK)/mitogen-activated protein kinase (MAPK) signaling pathways. Further bioinformatic analyses showed most of the androgen-sensitive microsome-associated protein networks play roles in cell proliferation and differentiation. Functional validation experiments showed that the androgen-sensitive microsome-associated proteins Janus kinase 2 (JAK2) and I-kappa B kinase complex-associated protein (IKAP) modulated the expression of prostate epithelial and neuronal markers, attenuated proliferation through an androgen receptor-dependent mechanism, and co-regulated androgen receptor-mediated transcription in LNCaP cells. Further biochemical analyses showed that the increased proliferation in JAK2 knockdown cells was mediated by activation of the mammalian target of rapamycin (mTOR), as determined by increased phosphorylation of several downstream targets (p70 S6 kinase, translational repressor 4E-BP1, and 40S ribosomal S6 protein). We conclude that the expression of microsome-associated proteins that were previously implicated in the tumorigenesis of prostate epithelial cells is strongly influenced by androgens. These findings provide a molecular framework for exploring the mechanisms underlying prostate tumorigenesis and how these protein networks might be attenuated or potentiated in disrupting the growth and survival of human prostate cancers.

Metabolomic profiling reveals a role for androgen in activating amino acid metabolism and methylation in prostate cancer cells

Prostate cancer is the second leading cause of cancer related death in American men. Development and progression of clinically localized prostate cancer is highly dependent on androgen signaling. Metastatic tumors are initially responsive to anti-androgen therapy, however become resistant to this regimen upon progression. Genomic and proteomic studies have implicated a role for androgen in regulating metabolic processes in prostate cancer. However, there have been no metabolomic profiling studies conducted thus far that have examined androgen-regulated biochemical processes in prostate cancer. Here, we have used unbiased metabolomic profiling coupled with enrichment-based bioprocess mapping to obtain insights into the biochemical alterations mediated by androgen in prostate cancer cell lines. Our findings indicate that androgen exposure results in elevation of amino acid metabolism and alteration of methylation potential in prostate cancer cells. Further, metabolic phenotyping studies confirm higher flux through pathways associated with amino acid metabolism in prostate cancer cells treated with androgen. These findings provide insight into the potential biochemical processes regulated by androgen signaling in prostate cancer. Clinically, if validated, these pathways could be exploited to develop therapeutic strategies that supplement current androgen ablative treatments while the observed androgen-regulated metabolic signatures could be employed as biomarkers that presage the development of castrate-resistant prostate cancer.

Model-based discovery of circulating biomarkers

Proteomic-based biomarker discovery approaches broadly attempt to identify proteins whose basal abundance, or change in abundance in response to a perturbation (e.g., a therapeutic intervention) is able to discriminate between populations of patients. Up until recently, the majority of approaches for discovering circulating biomarkers have focused on directly profiling serum or plasma to identify such proteins. However, the complexity and dynamic range of protein abundance in serum and plasma create a significant challenge for proteomics methods. To overcome these barriers, diverse approaches to simplify or to fractionate serum and plasma have been developed. For some diseases, such as those related to specific organs, there may be useful marker proteins that originate in the organ. Here, we describe an approach for marker discovery that focuses on the profiling of either primary tissue or cell culture models thereof.

Proteomic interrogation of androgen action in prostate cancer cells reveals roles of aminoacyl tRNA synthetases

Prostate cancer remains the most common malignancy among men in United States, and there is no remedy currently available for the advanced stage hormone-refractory cancer. This is partly due to the incomplete understanding of androgen-regulated proteins and their encoded functions. Whole-cell proteomes of androgen-starved and androgen-treated LNCaP cells were analyzed by semi-quantitative MudPIT ESI- ion trap MS/MS and quantitative iTRAQ MALDI- TOF MS/MS platforms, with identification of more than 1300 high-confidence proteins. An enrichment-based pathway mapping of the androgen-regulated proteomic data sets revealed a significant dysregulation of aminoacyl tRNA synthetases, indicating an increase in protein biosynthesis- a hallmark during prostate cancer progression. This observation is supported by immunoblot and transcript data from LNCaP cells, and prostate cancer tissue. Thus, data derived from multiple proteomics platforms and transcript data coupled with informatics analysis provides a deeper insight into the functional consequences of androgen action in prostate cancer.

Differential proteomics in the aging Noble rat ventral prostate

Incidence of prostatic diseases increases dramatically with age which may be related to a decline in androgen support. However, the key mechanisms underlying prostate aging remain unclear. In the present study, we investigated the aging process in the ventral prostate (VP) of Noble rats by identifying differentially expressed prostate proteins between 3- and 16-month-old animals using ICAT and MS. In total, 472 proteins were identified with less than a 1% false positive rate, among which 34 were determined to have a greater than two-fold increase or 1.7-fold decrease in expression in the aged VPs versus their younger counterparts. The majority of the differentially expressed proteins identified have not been previously reported to be associated with prostate aging, and they fall into specific functional categories, including oxidative stress/detoxification, chaperones, protein biosynthesis, vesicle transport, and intracellular trafficking. The expression of GST, ferritin, clusterin, kininogen, oxygen regulated protein 150, spermidine synthase, ADP ribosylation factor, and cyclophilin B was verified by Western blot analyses on samples used for the ICAT study, as well as on those obtained from an independent group of animals comprised of three age groups. To the best of our knowledge, this is the first study on the proteome of the aging rat prostate.

Precursor-ion mass re-estimation improves peptide identification on hybrid instruments

Mass spectrometry-based proteomics experiments have become an important tool for studying biological systems. Identifying the proteins in complex mixtures by assigning peptide fragmentation spectra to peptide sequences is an important step in the proteomics process. The 1-2 ppm mass-accuracy of hybrid instruments, like the LTQ-FT, has been cited as a key factor in their ability to identify a larger number of peptides with greater confidence than competing instruments. However, in replicate experiments of an 18-protein mixture, we note parent masses deviate 171 ppm, on average, for ion-trap data directed identifications and 8 ppm, on average, for preview Fourier transform (FT) data directed identifications. These deviations are neither caused by poor calibration nor by excessive ion-loading and are most likely due to errors in parent mass estimation. To improve these deviations, we introduce msPrefix, a program to re-estimate a peptide's parent mass from an associated high-accuracy full-scan survey spectrum. In 18-protein mixture experiments, msPrefix parent mass estimates deviate only 1 ppm, on average, from the identified peptides. In a cell lysate experiment searched with a tolerance of 50 ppm, 2295 peptides were confidently identified using native data and 4560 using msPrefixed data. Likewise, in a plasma experiment searched with a tolerance of 50 ppm, 326 peptides were identified using native data and 1216 using msPrefixed data. msPrefix is also able to determine which MS/MS spectra were possibly derived from multiple precursor ions. In complex mixture experiments, we demonstrate that more than 50% of triggered MS/MS may have had multiple precursor ions and note that spectra with multiple candidate ions are less likely to result in an identification using TANDEM. These results demonstrate integration of msPrefix into traditional shotgun proteomics workflows significantly improves identification results.

Labeling and identification of LNCaP cell surface proteins: a pilot study

BACKGROUND

Membrane proteins provide the interface between the cell and its environment and are responsible for cell adhesion, mobility, and intracellular signaling. Previous studies have focused on the LNCaP whole cell proteome and transcriptome but little is known about proteins at the prostate cell membrane and how they change in response to androgens.

MATERIALS AND METHODS

Following treatment with R1881 or vehicle, membrane proteins of the prostate cancer LNCaP cell line were tagged with biotin using EZ-link sulfo-NHS-LC-biotin. Using the tag membrane proteins were purified and separated using two-dimensional gel electrophoresis and identified using mass spectrometry. E-cadherin and low density lipoprotein receptor (LDLR) were used as positive controls and also investigated following bicalutamide treatment. Membrane localization and androgen-regulation of proteins was confirmed using sub-cellular fractionation, Western blotting and microscopy.

RESULTS

We have demonstrated efficient and specific protein biotinylation and purification of LNCaP plasma membrane proteins using Western analysis. E-cadherin and LDLR were regulated at the cell surface in response to R1881 and bicalutamide. Mass spectrometry identified several androgen-regulated membrane associated proteins including Prx-3 and GRP78 which are known to localize to other cellular compartments as well as the plasma membrane. We confirmed the localization of the identified proteins in LNCaP cells by co-localization with E-cadherin and immunohistochemistry of prostate tissue.

CONCLUSION

Cell surface biotinylation is an effective technique for identifying membrane proteins in the LNCaP prostate cancer cell line. We have demonstrated the identification of androgen-regulated membrane proteins and their validation in tissue samples.

Soy isoflavones exert differential effects on androgen responsive genes in LNCaP human prostate cancer cells

The high consumption of soy isoflavones in Asian diets has been correlated to a lower incidence of clinically important cases of prostate cancer. This study characterized the effects of a soy-derived isoflavone concentrate (ISF) on growth and gene expression profiles in the LNCaP, an androgen-sensitive human prostate cancer cell line. ISF caused a dose-dependent decrease in viability (P < 0.05) and DNA synthesis (P < 0.01), as well as an accumulation of cells in G(2)/M, and G(0)/G(1) phases of the cell cycle compared with controls. Using Affymetrix oligonucleotide DNA microarrays (U133A), we determined that ISF upregulated 80 genes and downregulated 33 genes (P < 0.05) involving androgen-regulated genes and pathways controlling cell cycle, metabolism, and intracellular trafficking. Changes in the expression of the genes of interest, identified by microarrays, were validated by Western immunoblot, Northern blot, and luciferase reporter assays. Prostate-specific antigen, homeobox protein NKX3, and cyclin B mRNA were significantly reduced, whereas mRNA was significantly upregulated for p21(CIP1), a major cell cycle inhibitory protein, and fatty acid and cholesterol synthesis pathway genes. ISF also significantly increased cyclin-dependent kinase inhibitor p27(KIP1) and FOXO3A/FKHRL1, a forkhead transcription factor. A differential pattern of androgen-regulated genes was apparent with genes involved in prostate cancer progression being downregulated by ISF, whereas metabolism genes were upregulated. In summary, we found that ISF inhibits the growth of LNCaP cells through the modulation of cell cycle progression and the differential expression of androgen-regulated genes. Thus, ISF treatment serves to identify new therapeutic targets designed to prevent proliferation of malignant prostate cells.

Identification of Putative Androgen Receptor Interaction Protein Modules

We have developed a novel androgen receptor (AR) expression system in the 293 human embryonic kidney cell line that recapitulates AR biochemical activity as a steroid hormone receptor in prostate cancer cells. We used this system to identify putative AR-binding proteins in the cytosolic and nuclear compartments of mammalian cells using a large scale co-immunoprecipitation strategy coupled to quantitative mass spectrometry. For example, the heat shock 70 and 90 chaperones, which are known regulators of steroid hormone receptor, were identified as AR-binding proteins. AR purification enriched for proteins involved in RNA processing, protein transport, and cytoskeletal organization, suggesting a functional link between AR and these protein modules in mammalian cells. For example, AR purification in the nuclear compartment led to the specific enrichment of alpha-actinin-4, clathrin heavy chain, and serine-threonine protein kinase C delta. Short interfering RNA knockdown studies and co-transcriptional reporter assays revealed that clathrin heavy chain possessed co-activator activity during AR-mediated transcription, whereas alpha-actinin-4 and protein kinase C delta displayed both co-activator and co-repressor activity during AR-mediated transcription that was dependent upon their relative expression levels. Lastly immunohistochemical staining of prostate tissue showed that alpha-actinin-4 levels decreased in the nucleus of high grade cancerous prostate samples, suggesting its possible deregulation in advanced prostate cancers as previously observed in late stage metastatic breast cancers. Taken together, these findings suggest AR binds to specific protein modules in mammalian cells and that these protein modules may provide a molecular framework for interrogating AR function in normal and cancerous prostate epithelial cells.

Evaluation of anin vitro model of androgen ablation and identification of the androgen responsive proteome in LNCaP cells

Proteins responsive to androgen and anti-androgen may be involved in the development and progression of prostate cancer and the ultimate failure of androgen-ablation therapy. These proteins represent potential diagnostic and therapeutic targets for improved management of prostate cancer. We have investigated the effect of androgen (R1881) and anti-androgen (bicalutamide) on the androgen-responsive prostate cancer LNCaP cell line using a quantitative gel-based proteomic approach. Prior to analysis, the in vitro system was evaluated for reproducibility and validated by appropriate molecular responses to treatment. Six replicate samples were independently generated and analysed by 2-D DIGE. According to strict statistical criteria, 197 spots were differentially expressed, of which we have successfully identified 165 spots corresponding to 125 distinct proteins. Following androgen supplementation, 108 spots (68 proteins) were increased and 57 spots (39 proteins) were decreased. Essentially no difference was observed between control and anti-androgen-treated samples, confirming the absence of "off-target" effects of bicalutamide. Identified proteins were involved in diverse processes including the stress response and intracellular signalling. The potential contribution to disease of these processes and identified constituent proteins are discussed. This rigorous, statistically supported study of androgen responses has provided a number of potential candidates for development as diagnostic/prognostic markers and drug targets.

Computational prediction of proteotypic peptides for quantitative proteomics

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Although such analyses typically assume that a protein's peptide fragments are observed with equal likelihood, only a few so-called 'proteotypic' peptides are repeatedly and consistently identified for any given protein present in a mixture. Using >600,000 peptide identifications generated by four proteomic platforms, we empirically identified >16,000 proteotypic peptides for 4,030 distinct yeast proteins. Characteristic physicochemical properties of these peptides were used to develop a computational tool that can predict proteotypic peptides for any protein from any organism, for a given platform, with >85% cumulative accuracy. Possible applications of proteotypic peptides include validation of protein identifications, absolute quantification of proteins, annotation of coding sequences in genomes, and characterization of the physical principles governing key elements of mass spectrometric workflows (e.g., digestion, chromatography, ionization and fragmentation).

Quantitative proteomic analysis of the budding yeast cell cycle using acid-cleavable isotope-coded affinity tag reagents

Quantitative profiling of proteins, the direct effectors of nearly all biological functions, will undoubtedly complement technologies for the measurement of mRNA. Systematic proteomic measurement of the cell cycle is now possible by using stable isotopic labeling with isotope-coded affinity tag reagents and software tools for high-throughput analysis of LC-MS/MS data. We provide here the first such study achieving quantitative, global proteomic measurement of a time-course gene expression experiment in a model eukaryote, the budding yeast Saccharomyces cerevisiae, during the cell cycle. We sampled 48% of all predicted ORFs, and provide the data, including identifications, quantitations, and statistical measures of certainty, to the community in a sortable matrix. We do not detect significant concordance in the dynamics of the system over the time-course tested between our proteomic measurements and microarray measures collected from similarly treated yeast cultures. Our proteomic dataset therefore provides a necessary and complementary measure of eukaryotic gene expression, establishes a rich database for the functional analysis of S. cerevisiae proteins, and will enable further development of technologies for global proteomic analysis of higher eukaryotes.

Gel-free mass spectrometry-based high throughput proteomics: Tools for studying biological response of proteins and proteomes

Revolutionary advances in biological mass spectrometry (MS) have provided a basic tool to make possible comprehensive proteomic analysis. Traditionally, two-dimensional gel electrophoresis has been used as a separation method coupled with MS to facilitate analysis of complex protein mixtures. Despite the utility of this method, the many challenges of comprehensive proteomic analysis has motivated the development of gel-free MS-based strategies to obtain information not accessible using two-dimensional gel separations. These advanced strategies have enabled researchers to dig deeper into complex proteomes, gaining insights into the composition, quantitative response, covalent modifications and macromolecular interactions of proteins that collectively drive cellular function. This review describes the current state of gel-free, high throughput proteomic strategies using MS, including (i) the separation approaches commonly used for complex mixture analysis; (ii) strategies for large-scale quantitative analysis; (iii) analysis of post-translational modifications; and (iv) recent advances and future directions. The use of these strategies to make new discoveries at the proteome level into the effects of disease or other cellular perturbations is discussed in a variety of contexts, providing information on the potential of these tools in electromagnetic field research.

Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues

Successful treatment of multiple cancer types requires early detection and identification of reliable biomarkers present in specific cancer tissues. To test the feasibility of identifying proteins from archival cancer tissues, we have developed a methodology, termed direct tissue proteomics (DTP), which can be used to identify proteins directly from formalin-fixed paraffin-embedded prostate cancer tissue samples. Using minute prostate biopsy sections, we demonstrate the identification of 428 prostate-expressed proteins using the shotgun method. Because the DTP method is not quantitative, we employed the absolute quantification method and demonstrate picogram level quantification of prostate-specific antigen. In depth bioinformatics analysis of these expressed proteins affords the categorization of metabolic pathways that may be important for distinct stages of prostate carcinogenesis. Furthermore, we validate Wnt-3 as an upregulated protein in cancerous prostate cells by immunohistochemistry. We propose that this general strategy provides a roadmap for successful identification of critical molecular targets of multiple cancer types.

Selective Isolation of Lysine-Free Tryptic Peptides Delimited by Arginine Residues: A New Tool for Proteome Analysis

Tryptic digestion of biotinylated Lys-C peptides followed by affinity chromatography allows the selective isolation of lysine-free tryptic peptides delimited by arginine residues (RRnK peptides). In silico analysis revealed that RRnK peptides represent 87% of the whole proteomes and their specific isolation simplifies the complex peptide mixture (5 peptides per protein). The good recoveries and high selectivity obtained in the isolation of RRnK peptides anticipate the applicability of this method in 2DE-free quantitative proteome analyses.

Proteomics in prostate cancer

PURPOSE OF REVIEW

State-of-the-art proteomics technologies are currently being assessed for utility in the study of prostatic malignancy. This review aims to provide background information on the current proteomics techniques employed in prostate cancer research, recent reports showing the potential application of proteomics in urological practice, and the future direction of proteomics in prostate cancer research and management.

RECENT FINDINGS

Proteomic profiling of serum as a diagnostic tool and a platform for biomarker discovery in prostate cancer continues to draw favorable attention as well as close scrutiny as technological enhancements and multi-center study results are reported. In-vitro studies on prostate cell lines provide positive proof-of-principle results. The application of proteomics to query prostate tissue specimens yields novel prostate cancer biomarkers requiring further validation. The integration of proteomics with immunology also yields promising findings that may translate into clinically relevant biological assays.

SUMMARY

The study of proteomics is an emerging research field, and current studies continue to display potential future usage in prostate cancer management. Succeeding scientific investigations will probably yield new diagnostic and prognostic tools for prostate cancer, provide insights into its underlying biology, and contribute to the development of novel treatment strategies.

ICAT-MS-MS time course analysis of atrophying mouse skeletal muscle cytosolic subproteome

Skeletal muscle atrophy is a process in which protein degradation exceeds protein synthesis, resulting in a decrease of the muscle's physiological cross-sectional area and mass, and is often a serious consequence of numerous health problems. We used the isotope-coded affinity tag (ICAT) labelling approach and MS-MS to protein profile cytosolic subcellular fractions from mouse tibialis anterior skeletal muscle undergoing 0, 4, 8, or 16 days of immobilisation-induced atrophy. For the validation of peptide and protein identifications statistical algorithms were applied to the sequence database search results in order to obtain consistent sensitivity/error rates for protein and peptide identifications at each immobilisation time point. In this study, we identified and quantified a large number of mouse skeletal muscle proteins. At a protein probability (P) of P> or = 0.9 (corresponding to a false positive error rate of less than 1%) 807 proteins were identified (231, 226, 217 for 4, 8, 16 days of immobilisation and 133 for the control sample, respectively), from which 51 displayed altered protein abundance with atrophy. Due to randomness of data acquisition, a full time course could be generated only for 62 proteins, most of which displayed unchanged protein abundance. In spite of this, useful information about dataset characteristics and underlying biological processes could be obtained through gene over-representation analysis. 20 gene categories-mainly but not exclusively encoded by the subset of overlapping proteins--were consistently found to be significantly (p < 0.05) over-represented in all 4 sub-datasets.

What can proteomic analyses contribute to understanding the molecular biology and clinical behavior of prostate cancer?

Identifying the proteins and their complex interactions that promote and/or sustain the aggressive malignant phenotype is essential for understanding key effectors of the molecular biology of prostate cancer. This is also essential for development of new clinical applications. A variety of proteomic techniques, ranging from mass spectrometry to new methods of multiplexing protein identification, have great potential for rapidly achieving these goals. However, in order to obtain meaningful results, these techniques must be applied within the context of our knowledge of the heterogeneity of prostate tissues and tumors, the impact of specimen processing on both the quality and quantity of proteins detected and a thorough understanding of prostate cell biology. Collaboration between the protein chemist and the prostate cell biologist will expedite progress in this important field.

Mass Spectrometry-based Expression Profiling of Clinical Prostate Cancer

The maturation of MS technologies has provided a rich opportunity to interrogate protein expression patterns in normal and disease states by applying expression protein profiling methods. Major goals of this research strategy include the identification of protein biomarkers that demarcate normal and disease populations, and the identification of therapeutic biomarkers for the treatment of diseases such as cancer (Celis, J. E., and Gromov, P. (2003) Proteomics in translational cancer research: Toward an integrated approach. Cancer Cell 3, 9-151). Prostate cancer is one disease that would greatly benefit from implementing MS-based expression profiling methods because of the need to stratify the disease based on molecular markers. In this review, we will summarize the current MS-based methods to identify and validate biomarkers in human prostate cancer. Lastly, we propose a reverse proteomic approach implementing a quantitative MS research strategy to identify and quantify biomarkers implicated in prostate cancer development. With this approach, the absolute levels of prostate cancer biomarkers will be identified and quantified in normal and diseased samples by measuring the levels of native peptide biomarkers in relation to a chemically identical but isotopically labeled reference peptide. Ultimately, a centralized prostate cancer peptide biomarker expression database could function as a repository for the identification, quantification, and validation of protein biomarker(s) during prostate cancer progression in men.

High throughput proteome screening for biomarker detection

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.

N-Terminal Isotope Tagging Strategy for Quantitative Proteomics: Results-Driven Analysis of Protein Abundance Changes

Comparing the relative abundance of each protein present in two or more complex samples can be accomplished using isotope-coded tags incorporated at the peptide level. Here we describe a chemical labeling strategy for the incorporation of a single isotope label per peptide, which is completely sequence-independent so that it potentially labels every peptide from a protein including those containing posttranslational modifications. It is based on a gentle chemical labeling strategy that specifically labels the N-terminus of all peptides in a digested sample with either a d5- or d0-propionyl group. Lysine side chains are blocked by guanidination prior to N-terminal labeling to prevent the incorporation of multiple labels. In this paper, we describe the optimization of this N-terminal isotopic tagging strategy and validate its use for peptide-based protein abundance measurements with a 10-protein standard mixture. Using a results-driven strategy, which targets proteins for identification based on MALDI TOF-MS analysis of isotopically labeled peptide pairs, we also show that this labeling strategy can detect a small number of differentially expressed proteins in a mixture as complex as a yeast cell lysate. Only peptides that show a difference in relative abundance are targeted for identification by tandem MS. Despite the fact that many peptides are quantitated, only those few showing a difference in abundance are targeted for protein identification. Proteins are identified by either targeted LC-ES MS/MS or MALDI TOF/TOF. Identifications can be accomplished equally well by either technique on the basis of multiple peptides. This increases the confidence level for both identification and quantitation. The merits of ES MS/MS or MALDI MS/MS for protein identification in a results-driven strategy are discussed.

Proteomics in pathology research

Proteomics is a multifaceted approach to study various aspects of protein expression, post-translational modification, interactions, organization and function at a global level. While DNA constitutes the 'information archive of the genome', it is the proteins that actually serve as the functional effectors of cellular processes. Thus, analysis of protein derangements on a proteome-wide scale will reveal insights into deregulated pathways and networks involved in the pathogenesis of disease. Although the field of proteomics has advanced tremendously in recent years, there are significant technical challenges that pose limitations to the routine application of mass spectrometry to clinical research. Despite these challenges, proteomic studies have yielded unparalleled information and understanding of the cellular biology of diseased states. The application of mass spectrometry to the study of diseases will ultimately lead to identification of biomarkers that are critical for the detection, diagnosis, prognosis and treatment of specific disease entities.