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.     

Discovery of putative oocyte quality markers by comparative ExacTag proteomics

Purpose: Identification of the biomarkers of oocyte quality, and developmental and reprogramming potential is of importance to assisted reproductive technology in humans and animals. Experimental design: PerkinElmer ExacTag? Kit was used to label differentially proteins in pig oocyte extracts (oocyte proteome) and pig oocyte‐conditioned in vitro maturation media (oocyte secretome) obtained with high‐ and low‐quality oocytes. Results: We identified 16 major proteins in the oocyte proteome that were expressed differentially in high‐ versus low‐quality oocytes. More abundant proteins in the high‐quality oocyte proteome included kelch‐like ECH‐associated protein 1 (an adaptor for ubiquitin‐ligase CUL3), nuclear export factor CRM1 and ataxia‐telangiectasia mutated protein kinase. Dystrophin (DMD) was more abundant in low‐quality oocytes. In the secretome, we identified 110 proteins, including DMD and cystic fibrosis transmembrane conductance regulator, two proteins implicated in muscular dystrophy and cystic fibrosis, respectively. Monoubiquitin was identified in the low‐quality‐oocyte secretome. Conclusions and clinical implications: A direct, quantitative proteomic analysis of small oocyte protein samples can identify potential markers of oocyte quality without the need for a large amount of total protein. This approach will be applied to discovery of non‐invasive biomarkers of oocyte quality in assisted human reproduction and in large animal embryo transfer programs.     

iTRAQ‐Based Quantitative Proteomic Analyses of High Grade Esophageal Squamous Intraepithelial Neoplasia

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and is the fourth most lethal cancer in China. Little is known about the proteome of high grade esophageal squamous intraepithelial neoplasia (HGN), which is a premalignant lesion of ESCC. A quantitative proteomic analysis using an isobaric tag for relative and absolute quantification (iTRAQ) approach is used to characterize the protein expression profiles in HGN. Among the 3156 identified proteins, a total of 236 proteins are discovered to be differentially expressed. Compared with paired normal esophageal epithelial tissues, 138 proteins are upregulated and 98 proteins are downregulated in HGN. Bioinformatics analyses are performed according to gene ontology, clusters of orthologous groups, and kyoto encyclopedia of genes and genomes enrichment analyses. Six differentially expressed proteins are chosen and validated by Western blotting. The results of the study increase our understanding of early tumorigenesis during ESCC, and provide insights into the proteome at the initial stages of the disease that can be used to identify potential biomarkers for early diagnosis and for therapeutic targets.     

Differential protein expression between normal, early-stage, and late-stage myxomatous mitral valves from dogs

Valvular heart disease accounts for over 20 000 deaths and 90 000 hospitalizations yearly in the United States. Myxomatous valve disease (MVD) is the most common disease of the mitral valve in humans and dogs. MVD is pathologically identical in these species and its pathogenesis is poorly understood. The objectives of this study were to (i) develop proteomic methodology suitable for analysis of extracellular matrix‐rich heart valve tissues and (ii) survey over‐ and under‐expressed proteins that could provide mechanistic clues into the pathogenesis of MVD. Normal, early‐stage, and late‐stage myxomatous mitral valves from dogs were studied. A shotgun proteomic analysis was used to quantify differential protein expression. Proteins were classified by function and clustered according to differential expression patterns. More than 300 proteins, with 117 of those being differentially expressed, were identified. Hierarchical sample clustering of differential protein profiles showed that early‐ and late‐stage valves were closely related. This finding suggests that proteome changes occur in early degeneration stages and these persist in late stages, characterizing a diseased proteome that is distinct from normal. Shotgun proteome analysis of matrix‐rich canine heart valves is feasible, and should be applicable to human heart valves. This study provides a basis for future investigations into the pathogenesis of MVD.     

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.     

Dynamic urinary proteomic analysis reveals stable proteins to be potential biomarkers

Human urinary proteome analysis is a convenient and efficient approach for understanding disease processes affecting the kidney and urogenital tract. Many potential biomarkers have been identified in previous differential analyses; however, dynamic variations of the urinary proteome have not been intensively studied, and it is difficult to conclude that potential biomarkers are genuinely associated with disease rather then simply being physiological proteome variations. In this paper, pooled and individual urine samples were used to analyze dynamic variations in the urinary proteome. Five types of pooled samples (first morning void, second morning void, excessive water‐drinking void, random void, and 24 h void) collected in 1 day from six volunteers were used to analyze intra‐day variations. Six pairs of first morning voids collected a week apart were used to study inter‐day, inter‐individual, and inter‐gender variations. The intra‐day, inter‐day, inter‐individual, and inter‐gender variation analyses showed that many proteins were constantly present with relatively stable abundances, and some of these had earlier been reported as potential disease biomarkers. In terms of sensitivity, the main components of the five intra‐day urinary proteomes were similar, and the second morning void is recommended for clinical proteome analysis. The advantages and disadvantages of pooling samples are also discussed. The data presented describe a pool of stable urinary proteins seen under different physiological conditions. Any significant qualitative or quantitative changes in these stable proteins may mean that such proteins could serve as potential urinary biomarkers.     

Utilizing endoscopic technology to reveal real-time proteomic alterations in response to chemoprevention

Cancer chemoprevention approaches use either pharmacological or dietary agents to impede, arrest or reverse the carcinogenic process. Although several agents have shown effectiveness against colon cancer, present intervention strategies provide only partial reduction. In this study, we utilized high-resolution endoscopy to obtain colon tumor biopsy specimens from Apc mutant mice before and after 2-wk sulindac intervention. To acquire information beyond genomics, proteome analysis using the ProteomeLab PF2D platform was implemented to generate 2-D protein expression maps from biopsies. Chromatograms produced common signature profiles between sulindac and nonsulindac treated samples, and contrasting profiles termed "fingerprints". We selected a double peak that appeared in tumor biopsies from sulindac-treated mice. Further analyses using MS sequencing identified this protein as histone H2B. The location of H2B in the 1(st) dimension strongly suggested PTM, consistent with identification of two oxidized methionines. While further studies on sulindac proteomic fingerprints are underway, this study demonstrates the feasibility and advantages of "real-time" proteomic analysis for obtaining information on biomarker discovery and drug activity that would not be revealed by a genetic assay. This approach should be broadly applicable for assessing lesion responsiveness in a wide range of translational and human clinical studies.     

An evaluation of multidimensional fingerprinting in the context of clinical proteomics

Multidimensional fingerprinting (MDF) utilizes measurable peptide characteristics to identify proteins. In this study, 3‐D fingerprinting, namely, parent protein molecular weight, peptide mass, and peptide retention time on RPLC, is used to identify 331 differentially expressed proteins between normal and human colon cancer plasma membrane samples. A false discovery rate (FDR) procedure is introduced to evaluate the performance of MDF on the colon cancer dataset. This evaluation establishes a false protein identification rate below 15% for this dataset. Western blot analysis is performed to validate the differential expression of the MDF‐identified protein VDAC1 on the original tissue samples. The limits of MDF are further assessed by a simulation study where key parameters such as database size, query size, and mass accuracy are varied. The results of this simulation study demonstrate that fingerprinting with three dimensions yields low FDR values even for large queries on the complete human proteome without the need for prior peptide sequencing by tandem mass spectrometry. Specifically, when mass accuracy is 10 ppm or lower, full human proteome searches can achieve FDR values of 10% or less.     

An application of the 2-nitrobenzenesulfenyl method to proteomic profiling of human colorectal carcinoma: A novel approach for biomarker discovery

In the development of novel biomarkers, the proteomic approach is advantageous because using it the cancer-associated proteins can be directly identified. We previously developed a 2-nitrobenzenesulfenyl (NBS) method to improve quantitative proteome analysis. Here, we applied this method to proteomic profiling of colorectal carcinoma (CRC) to identify novel proteins with altered expression in CRC. Each pair of tumor and normal tissue specimens from 12 CRC patients was analyzed, and approximately 5000 NBS-labeled paired peaks were quantified. Peaks with altered signal intensities (>1.5-fold) and occurring frequently in the samples (>70%) were selected, and 128 proteins were identified by MS/MS analyses as differentially expressed proteins in CRC tissues. Many proteins were newly revealed to be CRC related; 30 were reported in earlier studies of CRC. Six proteins that were up-regulated in CRC (ZYX, RAN, RCN1, AHCY, LGALS1, and VIM) were further characterized and validated by Western blot and immunohistochemistry. All six were found to be CRC-localized, either in cancer cells or in stroma cells near the cancer cells. These results indicate that the proteins identified in this study are novel candidates for CRC markers, and that the NBS method is useful in proteome mining to discover novel biomarkers.     

Effects of endurance exercise on the urinary proteome analyzed by 2-D PAGE and Orbitrap MS

Purpose : Exercise‐induced proteinuria is a well‐known phenomenon and the influence of parameters such as intensity and duration was studied extensively. Usually, total protein or albumin was measured for diagnosis of a proteinuria, and the present study was performed to search for qualitative differences in the urinary proteome before and after endurance exercise. Experimental design : Urine samples were concentrated and proteins separated by means of 2‐D PAGE. Proteins differing in the investigated groups were identified by nano‐UPLC‐Orbitrap MS after trypsin digestion. Results : The study yielded several proteins such as hemopexin, albumin, orosomucoid 1, transferrin or carbonic anhydrase 1 that were elevated after a marathon run in comparison to a control group. These are linked to physiological changes resulting from endurance exercise such as destruction of erythrocytes or increased fat metabolism. On the contrary, 2‐D PAGE profiles of athletes at rest did not differ from those of control samples. Conclusions and clinical relevance: The study is a starting point to build up individual 2‐D PAGE protein maps of athletes. Further studies will investigate intra‐individual differences and further exercise parameters, which potentially lead to a physiological monitoring system for athletes in training and competition and may also complement the blood passport in doping control.     

The variability in tissue proteomics

Variability is one of the most critical issues of concern in clinical proteomics. In this issue of Proteomics Clinical Applications, Yoshida et al. [Proteomics Clin. Appl. 2012, 6, 412-417] describe the effects of blood and number of washes on the human glomerular proteome isolated from the kidney by laser microdissection. The blood-derived proteins occupied almost 50% of all the identified proteins in the unwashed samples, whereas varying the number of washes (from 1-5) with PBS yielded only 43-80% of the proteins identified in each sample that were common in all samples. This urges caution to all proteomists to carefully consider sample preservation and preparation for tissue proteome analysis.     

Proteomic expression analysis and comparison of protein and mRNA expression profiles in human malignant gliomas

Gliomas are highly heterogeneous and therapy resistant tumors with a poor prognosis. Novel experimental therapeutic approaches have shown some promising results, but often target specific molecular mechanisms or antigens, and careful characterization of the molecular subgroup of the tumors will therefore likely be important. Thorough investigations of gene and protein alterations are also important to better understand the tumorigenic mechanisms. We have undertaken a proteomic approach, using 2-D DIGE and LC-MS/MS protein identification, to investigate 38 human gliomas and normal brains. We show that the proteome profile can discriminate between normal brain and tumors, and between tumors of varying grade by a supervised classifier. Furthermore, an analysis of the identified proteins shows an enrichment of proteins associated to pathways known to be central in gliomas, such as MEK/Erk signaling and actin cytoskeleton. It also shows a shift between different glial fibrillary acidic protein (GFAP) representatives in different grades. In a previous study the gene expression profile was characterized in an almost identical set of tumors, which enabled a paired analysis of the gene and protein expression profiles. We show that there is often a weak correlation between the mRNA and protein level. This, together with the ability of proteomics to identify PTMs, emphasizes the benefit of characterization on a protein level.     

Analysis of the human testis proteome by mass spectrometry and bioinformatics

The testis is a unique organ responsible for sperm production and androgen secretion in men. To analyze the human testis proteome on a large scale, 1-D SDS-PAGE and RP-LC-MS/MS were applied and 1430 proteins in the human testis were identified. Both the false-positive rate of peptides and protein identification confidence scores were calculated in the present study. Subsequent bioinformatics analysis of the human testis proteome revealed 39 testis-specific proteins which may be important for testis functions. And a large family of proteins were identified possibly involved in alternative splicing, which may also be involved in testis-specific splicing events and explain why splicing is so prevalent in the testis. Compared with the studies on brain proteome, researches on the testis proteome is still very limited. Studies of these proteins will give a better understanding on the function of the testis. Moreover, this large-scale identification of testis proteins in humans could serve as a reference for future studies on the mechanisms underlying male infertility, searching for potential contraceptive targets, and developing new treatments for testis cancer.     

Proteomic analysis of pericardial effusion: Characteristics of tuberculosis-related proteins

The aim of this study has been designed to identify the tuberculosis (TB)-related proteins in pericardial effusion by proteomic approaches. TB is one of the major infectious diseases causing pericardial effusion. This study details protein profiles in pericardial effusion from three TB patients and three heart failure patients. Pericardial effusions were analyzed using 2-DE combined with the nano-HPLC-ESI-MS/MS. Eleven protein spots with differential expression in pericardial effusion were identified between the two groups of TB and heart failure patients (the control group). Seven protein spots were upregulated and four were downregulated. The composition of the pericardial effusion proteome may reflect the pathophysiological conditions affecting the progression of tuberculous pericarditis. The proteins in the tuberculous pericardial effusion with differential expression may serve as new and direct indicators of drug treatment. A possible conclusion is indicated that fibrinogen may play an important role for fibrin assembly in tuberculous pericardial effusion.     

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.     

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.     

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.     

Proteomics cataloging analysis of human expressed prostatic secretions reveals rich source of biomarker candidates

Expressed prostatic secretions (EPS) contain proteins of prostate origin that may reflect the health status of the prostate and be used as diagnostic markers for prostate diseases including prostatitis, benign prostatic hyperplasia, and prostate cancer. Despite their importance and potential applications, a complete catalog of EPS proteins is not yet available. We, therefore, undertook a comprehensive analysis of the EPS proteome using 2‐D micro‐LC combined with MS/MS. Using stringent filtering criteria, we identified a list of 114 proteins with at least two unique‐peptide hits and an additional 75 proteins with only a single unique‐peptide hit. The proteins identified include kallikrein 2 (KLK2), KLK3 (prostate‐specific antigen), KLK11, and nine cluster of differentiation (CD) molecules including CD10, CD13, CD14, CD26, CD66a, CD66c, CD 143, CD177, and CD224. To our knowledge, this list represents the first comprehensive characterization of the EPS proteome, and it provides a candidate biomarker list for targeted quantitative proteomics analysis using a multiple reaction monitoring (MRM) approach. To help prioritize candidate biomarkers, we constructed a protein–protein interaction network of the EPS proteins using Cytoscape (www.cytoscape.org), and overlaid the expression level changes from the Oncomine database onto the network.