Targeted detection of prostate cancer proteins in serum using heavy‐isotope‐labeled‐peptide standards and MALDI‐TOF/TOF

Proteins released from cancer tissues to patient sera can potentially be used to achieve sensitive, specific, and early detection of cancer by means of blood tests. In this study, we used a platform that combines glycopeptide capture, heavy‐isotope‐labeled‐peptide standards, and liquid chromatography coupled to tandem mass spectrometry to determine which glycoproteins from prostate cancer can be detected in sera from patients with early‐stage prostate cancer. The detection limit for prostate‐specific antigen in serum was 3.44 ng/mL; thus, direct identification of low abundance, cancer‐specific proteins was achieved using our platform. We showed that prostatic acid phosphatase and membrane metallo‐endopeptidase that were detected in sera were preferentially expressed in prostate cancer tissues. Levels of these two proteins were elevated in biopsy‐positive patients but not biopsy‐negative groups. Therefore, these two proteins are candidate biomarkers for analysis of patient samples with levels of prostate‐specific antigen in the diagnostic gray zone.     

Towards a comprehensive proteome of normal and malignant human colon tissue by 2-D-LC-ESI-MS and 2-DE proteomics and identification of S100A12 as potential cancer biomarker

The aim of this study was to characterize the proteome of normal and malignant colonic tissue. We previously studied the colon proteome using 2‐DE and MALDI‐MS and identified 734 proteins (Roeßler, M., Rollinger, W., Palme S., Hagmann, M.‐L., et al.., Clin. Cancer Res. 2005, 11, 6550–6557). Here we report the identification of additional colon proteins from the same set of tissue samples using a complementary nano‐flow 2‐D‐LC‐ESI‐MS. In total, 484 proteins were identified in colon. Of these, 252 had also been identified by the 2‐DE/MALDI‐MS approach, whereas 232 proteins were unique to the 2‐D‐LC‐ESI‐MS analysis. Comparing protein expression in neoplastic and normal colon tissue indicated elevated expression of several proteins in colorectal cancer, among them the well established tumor marker carcinoembryonic antigen, as well as calnexin, 40S ribosomal protein S15a, serpin H1, and S100A12. Overexpression of these proteins was confirmed by immunoblotting. Serum levels of S100A12 were determined by ELISA and were found to be strongly elevated in colorectal cancer patients compared to healthy individuals. We conclude, that 2‐D‐LC‐ESI‐MS is a powerful approach to identify and compare protein profiles of tissue samples, that it is complementary to 2‐DE/MALDI‐MS approaches and has the potential to identify novel biomarkers.     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Investigation of an albumin‐enriched fraction of human serum and its albuminome

The removal of albumin and other high abundance proteins is a routine first step in the analysis of serum and plasma proteomes. However, as albumin can bind proteins and peptides, there is a universal concern as to how the serum proteome is changed by the removal of albumin. To address this concern, the current study was designed to identify proteins and peptides removed from the serum during albumin depletion; to determine which of these are bound to albumin (rather than copurified) and whether the bound proteins are intact proteins or peptide fragments. Sequential, independent analyses including both anti‐albumin antibody (anti‐HSA) affinity chromatography and SEC were used to isolate albumin‐bound proteins. RP‐HPLC and 1‐D SDS‐PAGE were then used to further separate the proteins prior to identification by MS/MS. Finally, whole protein molecular weight (MW) MS measurements coupled with protein coverage obtained by MS were combined to assess whether the bound proteins were intact or peptide fragments. Combining the results from multiple approaches, 35 proteins, of which 24 are intact, were found to be associated with albumin, and they include both known high and low abundance proteins.     

Proteomics in clinical prostate research

The incidence of early prostate cancer (PCa) has increased rapidly in recent years. The majority of newly diagnosed PCa are in early tumor phase. Presently, we do not have adequate biomarkers to assess tumor aggressiveness in individual cases. Consequently, too many patients are given curatively intended treatment. An exploration of the human proteome may provide clinically useful markers. 2-DE has been successfully used for analysis of the protein phenotype using clinical samples. Proteins are separated according to size and charge, gels are compared by image analysis, protein spots of interest are excised, and proteins identified by MS. This method is exploratory and allows protein identification. However, low-abundance proteins are difficult to detect and 2-DE is currently too labor-intensive for routine use. In recent years, nongel based techniques, such as LC-MS, SELDI-MS, and protein arrays have emerged. They require smaller sample sizes and can be more automated than 2-DE. In this review, we describe studies of the protein expression of benign prostatic tissue and PCa, which is likely to serve as the first step in prognostic biomarker discovery. The prostate proteome is still far from a complete mapping which would enhance our understanding of PCa biology.     

Salivary biomarkers associated with perceived satiety and body mass in humans

Regulation of food intake and energy homeostasis is controlled by a delicate balancing of numerous central and peripheral factors, including circulating peptide hormones. This study investigated the proteome of saliva using SELDI‐TOF‐MS in relation to satiety and body mass index (BMI) in humans. Within a longitudinal test session, 18 subjects were exposed to a lunch‐induced hunger‐satiety shift, while every 15 min collecting their whole saliva and rating their hunger and satiety. Saliva was analysed by SELDI‐TOF‐MS using IMAC arrays with a chromatographic copper surface (IMAC‐Cu). From all subjects and time points measured, peptide and protein profiles showed 190 common peaks. Their interrelationships show that 37% of the variation was accounted for in one dimension. About 30 means had a strong association (0.70<|r|<0.95) with all subjective satiety ratings across time during the test session, and seven peaks were significantly correlated to BMI. Database MS searches indicated characterisation of some relevant metabolic peptide hormones. In conclusion, SELDI‐TOF‐MS on human saliva provides a valuable and noninvasive way of profiling that enables characterisation of novel and differently expressed peptides and proteins which can be used as biomarkers of satiety and overweight.     

Shotgun proteomics identifies proteins specific for acute renal transplant rejection

Purpose: Acute rejection (AR) remains the primary risk factor for renal transplant outcome; development of non‐invasive diagnostic biomarkers for AR is an unmet need. Experimental design: We used shotgun proteomics applying LC‐MS/MS and ELISA to analyze a set of 92 urine samples, from patients with AR, stable grafts (STA), proteinuria (NS), and healthy controls. Results: A total of 1446 urinary proteins (UP) were identified along with a number of non‐specific proteinuria‐specific, renal transplantation specific and AR‐specific proteins. Relative abundance of identified UP was measured by protein‐level spectral counts adopting a weighted fold‐change statistic, assigning increased weight for more frequently observed proteins. We have identified alterations in a number of specific UP in AR, primarily relating to MHC antigens, the complement cascade and extra‐cellular matrix proteins. A subset of proteins (uromodulin, SERPINF1 and CD44), have been further cross‐validated by ELISA in an independent set of urine samples, for significant differences in the abundance of these UP in AR. Conclusions and clinical relevance: This label‐free, semi‐quantitative approach for sampling the urinary proteome in normal and disease states provides a robust and sensitive method for detection of UP for serial, non‐invasive clinical monitoring for graft rejection after kidney transplantation.     

Candidate antigens specifically detected by cerebrospinal fluid-IgG in oligoclonal IgG bands-positive multiple sclerosis patients

The aim of the present study was to detect antigenic proteins that react specifically with cerebrospinal fluid (CSF)-IgG from oligoclonal IgG bands (OB)-positive multiple sclerosis (MS) patients. To identify such antigenic proteins, we developed a rat brain proteome map using 2-DE and applied it to the immunoscreening of brain proteins that react with CSF-IgG but not with serum-IgG in OB-positive MS patients. After sequential MALDI-TOF mass spectrometry, eight proteins [two neuronal proteins (tubulin β-2 and γ enolase-2), HSP-1, Tpi-1 protein and cellular enzymes (creatine kinase, phosphopyruvate hydratase, triosephosphate isomerase and phosphoglycerate kinase-1)] were identified as candidate antigens in seven MS patients. Reactivity to tubulin was seen in Western blotting in four patients, and CSF-specific anti-tubulin IgG was detected in one patient. In addition, CSF-specific anti-gamma enolase IgG was found in another patient. These findings suggest that intrathecal immune responses may occur against a broad range of proteins in MS.     

Exploration of the normal human bronchoalveolar lavage fluid proteome

We obtained insight into normal lung function by proteome analysis of bronchoalveolar lavage fluid (BALF) from six normal human subjects using a "Lyse-N-Go' shotgun proteomic protocol. Intra-sample variation was calculated using three different label-free methods, (i) protein sequence coverage; (ii) peptide spectral counts and (iii) peptide single-ion current areas (PICA), which generates protein expression data by summation of the area under the curve for a given peptide single-ion current trace and then adding values for all peptides from that same parent protein. PICA gave the least intra-subject variability and was used to calculate differences in protein expression between the six subjects. We observed an average threefold inter-sample variability, which affects analysis of changes in protein expression that occur in different diseases. We detected 167 unique proteins with >100 proteins detected in each of the six individual BAL samples, 42 of which were common to all six subjects. Gene ontology analysis demonstrated enrichment of several biological processes in the lung, reflecting its expected role in gas exchange and host defense as an immune organ. The same biological processes were enriched compared to either plasma or total genome proteome, suggesting an active enrichment of plasma proteins in the lung rather than passive capillary leak.     

Discovery and validation of urinary biomarkers for prostate cancer

Only 30% of patients with elevated serum prostate specific antigen (PSA) levels who undergo prostate biopsy are diagnosed with prostate cancer (PCa). Novel methods are needed to reduce the number of unnecessary biopsies. We report on the identification and validation of a panel of 12 novel biomarkers for prostate cancer (PCaP), using CE coupled MS. The biomarkers could be defined by comparing first void urine of 51 men with PCa and 35 with negative prostate biopsy. In contrast, midstream urine samples did not allow the identification of discriminatory molecules, suggesting that prostatic fluids may be the source of the defined biomarkers. Consequently, first void urine samples were tested for sufficient amounts of prostatic fluid, using a prostatic fluid indicative panel (“informative” polypeptide panel; IPP). A combination of IPP and PCaP to predict positive prostate biopsy was evaluated in a blinded prospective study. Two hundred thirteen of 264 samples matched the IPP criterion. PCa was detected with 89% sensitivity, 51% specificity. Including age and percent free PSA to the proteomic signatures resulted in 91% sensitivity, 69% specificity.     

A qualitative proteome investigation of the sediment portion of human urine: Implications in the biomarker discovery process

Inherent to the biomarker discovery process is a comparative analysis of physiological states. It is therefore critical that the proteome detection protocol does not bias the analysis. With urine, the sediment portion, obtained upon thawing frozen urine, is routinely discarded prior to proteome analysis. However, our results demonstrate that such a practice inadvertently induces bias, having significant implications in the biomarker discovery process. We present the first proteome investigation of human urinary sediments, identifying 60 proteins in this phase by MS. Many sediment proteins were also detected in the urinary supernatant, indicating that several proteins partition between the two phases. This partitioning is dependant on the pH of the sample, as well as the degree of sample agitation. As a consequence of discarding the sediment portion of urine, the concentration of potential candidate biomarkers in the supernatant phase will be altered or, in other instances, may be completely removed from the sample. To minimize this, the pH of all samples should first be normalized, and the samples vigorously vortexed prior to discarding the sediments. For more comprehensive biomarker investigations, we suggest that urinary sediments be analyzed along with the supernatant proteins.     

The proteome of the human breast cancer cell line MDA-MB-231: Analysis by LTQ-Orbitrap mass spectrometry

We have used a combination of SDS-PAGE and LTQ-Orbitrap MS to explore the proteome of the highly invasive MDA-MB-231 breast cancer cell line. Based on about 520?000 MS/MS spectra, a total of 3481 proteins were identified and subsequently classified according to their cellular distribution and molecular function. Interestingly, a large proportion of proteins (38%) were from cellular membranes and we were able to characterize numerous proteins involved in cancer initiation and progression such as the tumor suppressor p53 and the epidermal growth factor receptor. Together, this study represents the largest proteome database of breast cancer cells realized to date and demonstrates the value of using Orbitrap MS for deeper proteome analysis.     

Disease proteomics of endocrine disorders revealed by two-dimensional gel electrophoresis and mass spectrometry

Endocrine disorders such as dwarfism and diabetes show abnormalities in many different organs even if a certain hormone is the primary cause of the disease. One of the aims of proteomics is to elucidate an abnormal hormone network underlying dysfunction in the disease through quantitative and qualitative proteome analyses of various organs. In a comprehensive study of the rdw rat with hereditary dwarfism, we found the accumulation of ER proteins in the rdw thyroid. Contrary to the initial notion that the dwarfism of the rat was caused by genetic mutations related to pituitary hormones, the primary cause is a missense mutation in the thyroglobulin gene. To understand at the protein level cellular damage caused by oxidative stress, we developed a proteomic method and applied to detecting protein carbonyls in various organs of a diabetes model OLETF rat. The method would provide a means toward clarifying a comprehensive view of oxidative modifications of proteins in diabetes. We review 2-DE-based disease proteomics of endocrine disorders in general, with particular attention paid to our proteome projects by a 2-DE method with an agarose IEF gel in the first dimension (agarose 2-DE) and LC-MS/MS.     

Multidimensional protein identification technology analysis highlights mitoxantrone‐induced expression modulations in the primary prostate cancer cell proteome

Chemotherapeutic agents as they are used today have limited effectiveness against prostate cancer, but may potentially be used in new combinations with more efficacious results. Mitoxantrone, used for palliation of prostate cancer, has recently been found by our group to improve the susceptibility of primary prostate cancer cells to killing through the Fas‐mediated death pathway. Here we used a shotgun proteomics approach to first profile the entire prostate cancer proteome and then identify specific factors involved in this mitoxantrone response. Peptides derived from primary prostate cancer cells treated with or without 100 nM mitoxantrone were analyzed by multidimensional protein identification technology (MudPIT). Strict limits and data filtering hierarchies were applied to identify proteins with high confidence. We identified 1498 proteins belonging to the prostate cancer proteome, 83 of which were significantly upregulated and 27 of which were markedly downregulated following mitoxantrone treatment. These proteins perform diverse functions, including ceramide production, tumour suppression, and oxidative reduction. Detailed proteomic analyses of prostate cancer cells and their response to mitoxantrone will further our understanding of its mechanisms of action. Identification of proteins influenced by treatment with mitoxantrone or other compounds may lead to the development of more effective drug combinations against prostate cancer.     

High-resolution biomarker discovery: Moving from large-scale proteome profiling to quantitative validation of lead candidates

Diverse proteomic techniques based on protein MS have been introduced to systematically characterize protein perturbations associated with disease. Progress in clinical proteomics is essential for personalized medicine, wherein treatments will be tailored to individual needs based on patient stratification using noninvasive disease monitoring procedures to reveal the most appropriate therapeutic targets. However, breakthroughs await the successful development and application of a robust proteomic pipeline capable of identifying and rigorously assessing the relevance of multiple candidate proteins as informative diagnostic and prognostic indicators or suitable drug targets involved in a pathological process. While steady progress has been made toward more comprehensive proteome profiling, the emphasis must now shift from in depth screening of reference samples to stringent quantitative validation of selected lead candidates in a broader clinical context. Here, we present an overview of the emerging proteomic strategies for high-throughput protein detection focused primarily on targeted MS/MS as the basis for biomarker verification in large clinical cohorts. We discuss the conceptual promise and practical pitfalls of these methods in terms of achieving higher dynamic range, higher throughput, and more reliable quantification, highlighting research avenues that merit additional inquiry.     

Identification of glial-cell-line-derived neurotrophic factor-regulated proteins of striatum in mouse model of Parkinson disease

Glial-cell-line-derived neurotrophic factor (GDNF) is a potent survival factor for dopaminergic neurons, and hence serves as a therapeutic candidate for the treatment of Parkinson's disease. However, despite the potential clinical and physiological importance of GDNF, its mechanism of action is unclear. Therefore, we employed a state-of-the-art proteomic technique, DIGE, along with MS and a bioinformatics tool called Database for Annotation, Visualization and Integrated Discovery (DAVID), to profile proteome changes in the parkinsonian mouse striatum after GDNF challenge. Forty-six unique differentially expressed proteins were successfully identified, which were found either up-regulated and/or down-regulated at the two time points 4 and 72 h compared with the control. Proteins involved in cell differentiation and system development formed the largest part of the proteins regulated under GDNF. Furthermore, the aberrant expression of HSPs and mitochondria-associated proteins were noticeable. Moreover, mitochondrial stress 70 protein and heat shock cognate 71 kDa protein, whose relative levels increased significantly in GDNF-treated striatum, were further evaluated with Western blot and RT-PCR, demonstrating a good agreement with quantitative proteomic data. These data will provide some clues for understanding the mechanisms by which GDNF promotes the survival of dopaminergic neurons.     

Analysis of the differential proteome of human erythroblasts during in vitro erythropoiesis by 2-D DIGE

In the present study we have used an in vitro culture system that induces differentiation of human CD34(+) cells down the erythroid lineage along with 2-D DIGE to determine the differential proteome of erythroblasts at specific developmental stages during erythropoiesis. We initially distinguished 154 proteins differentially expressed between pro-normoblasts and polychromatic/orthochromatic erythroblasts, of which 24 protein spots, representing 21 different proteins, were identified following MS/MS and verification in replicate experiments with cells from different individuals. These data were confirmed by analysis of the differential proteome of erythroblasts at more discrete stages of erythropoiesis using 2-D DIGE and by mapping the expression of three identified proteins (Annexin I, Annexin II, Carbonic Anhydrase I) throughout erythropoiesis by Western blot with specific antisera. In addition, the differential expression of proteins due to biological variation, such as polymorphism, was determined by comparing erythroblasts at the same developmental stage from different individuals; none of the proteins thus identified were represented in the above data set. Finally, we discuss the problems associated with 2-D DIGE gel-based proteomic approaches such as ours and suggest a modified approach for decreased inter-gel variation, improved protein resolution and increased protein concentration, which should significantly facilitate protein identification.