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.     

Systematic investigation of lycopene effects in LNCaP cells by use of novel large‐scale proteomic analysis software

Lycopene, the red pigment of tomatoes, is a carotenoid with potent antioxidant properties. Although lycopene may function as a prostate cancer chemoprevention agent, little is known about its effects at the cellular level. To define general changes induced by treatment of cells with lycopene, and to gain insights into the possible chemoprevention properties of lycopene, we investigated changes in protein expression after lycopene treatment in human LNCaP cells. The high throughput proteomics data were then visualized and analyzed by novel biological protein pathway modeling software. Differentially expressed proteins were identified, and the data were analyzed by protein pathway simulation software, without the need for specialized programming, by importing pathway models from a number of sources or by creating our own. One notable outcome was the identification of a group of upregulated proteins involved in detoxification of reactive oxygen species. This finding suggests that a possible mechanism of lycopene chemoprevention is the stimulation of detoxification enzymes associated with the antioxidant response element. Novel biological pathway modeling software enhances analysis of large proteomics data. When applied to the analysis of proteins differentially expressed in prostate cancer cells upon treatment with lycopene, the up‐regulation of detoxification enzymes was identified.     

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.     

An experimental strategy for quantitative analysis of the humoral immune response to prostate cancer antigens using natural protein microarrays

The identification of human tumor antigens has potential utility in the diagnosis and treatment of cancers. We demonstrate here a complete strategy to profile immunoreactivity and identify tumor antigens from proteins derived from tumor cell lines. Microarrays of proteins produced from 2-D LC fractionation of prostate tumor cell-line lysates were used to profile immunoreactivity in the sera of prostate cancer patients and control subjects. Cancer-associated immunoreactivity to distinct groups of chromatography fractions was present in about 50% of the patients, with greater immunoreactivity present in patients with non-organ-confined cancer than in patients with organ-confined cancer. We grouped the immunoreactive fractions by similarities in elution order and patterns of immunoreactivity to guide and interpret the MS analysis of selected fractions, which was used to identify the proteins that may be responsible for the immunoreactivity. As a complementary method to further characterize and validate the immunoreactivity of the proteins identified by mass spectrometry, we demonstrate the use of focused microarrays of recombinant proteins. Disease-associated immunoreactivity was confirmed for one of the identified proteins, human Kallikrein 11. These results demonstrate a practical approach to screening, identifying, and validating immunoreactive proteins that could be applied to diverse studies on humoral immune responses.     

Proteome alterations induced in human white blood cells by consumption of Brussels sprouts: Results of a pilot intervention study

Epidemiological studies indicate a correlation of cruciferous vegetables consumption with reduced incidence of cancer. This study was designed to investigate molecular mechanisms, which may help to understand the beneficial effects of Brussels sprout consumption. In order to avoid the limitations of in vitro model systems, we performed a dietary intervention study with five participants. We investigated, whether sprout consumption affects the proteome profile of primary white blood cells. In order to achieve maximal sensitivity in detecting specific adaptive proteome alterations, we metabolically labelled freshly isolated cells in the presence of ³⁵S‐methionine/cysteine and performed autoradiographic quantification of protein synthesis. Proteins were separated by 2‐DE and spots of interest were cut out, digested and identified by MS. After the intervention, we found a significant up‐regulation of the synthesis of manganese superoxide dismutase (1.56‐fold) and significant down‐regulation of the synthesis of heat shock 70 kDa protein (hsp70; 2.27‐fold). Both proteins play a role in malignant transformation of cells. Hsp‐70 is involved in the regulation of apoptosis, which leads to elimination of cancer cells, while SOD plays a key role in protection against reactive oxygen species mediated effects. Our findings indicate that the alteration of the synthesis of these proteins may be involved in the anticarcinogenic effects of cruciferous vegetables, which was observed in earlier laboratory studies with animals.     

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.     

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.     

Urine proteomics for profiling of human disease using high accuracy mass spectrometry

Knowledge of the biologically relevant components of human tissues has enabled the invention of numerous clinically useful diagnostic tests, as well as non-invasive ways of monitoring disease and its response to treatment. Recent use of advanced MS-based proteomics revealed that the composition of human urine is more complex than anticipated. Here, we extend the current characterization of the human urinary proteome by extensively fractionating urine using ultra-centrifugation, gel electrophoresis, ion exchange and reverse-phase chromatography, effectively reducing mixture complexity while minimizing loss of material. By using high-accuracy mass measurements of the linear ion trap-Orbitrap mass spectrometer and LC-MS/MS of peptides generated from such extensively fractionated specimens, we identified 2362 proteins in routinely collected individual urine specimens, including more than 1000 proteins not described in previous studies. Many of these are biomedically significant molecules, including glomerularly filtered cytokines and shed cell surface molecules, as well as renally and urogenitally produced transporters and structural proteins. Annotation of the identified proteome reveals distinct patterns of enrichment, consistent with previously described specific physiologic mechanisms, including 336 proteins that appear to be expressed by a variety of distal organs and glomerularly filtered from serum. Comparison of the proteomes identified from 12 individual specimens revealed a subset of generally invariant proteins, as well as individually variable ones, suggesting that our approach may be used to study individual differences in age, physiologic state and clinical condition. Consistent with this, annotation of the identified proteome by using machine learning and text mining exposed possible associations with 27 common and more than 500 rare human diseases, establishing a widely useful resource for the study of human pathophysiology and biomarker discovery.     

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.     

Intrinsic subtype-associated changes in the plasma proteome in breast cancer

Breast cancers are classified into five intrinsic subtypes: Luminal subtype A, Luminal subtype B, HER2+, Basal, and Normal-like. In this study, we compared the plasma proteome of patients with Luminal A, Luminal B, HER2+, and Basal subtype with plasma from healthy individuals. Protein changes were considered significant if q-value (false discovery rate) was less than 5%. The highest number of changes in the plasma proteome was observed in patients with Luminal type B followed by Basal type breast cancers. The plasma proteome of Luminal A and HER2+ breast cancer patients did not differ significantly from healthy individuals. In Basal breast cancer, a significant number of plasma proteins were downregulated compared with healthy individuals. Acute phase-response proteins α-glycoprotein orosomucoid 1 and serum amyloid protein P were specifically upregulated in the plasma of Luminal B breast cancer patients, suggesting prevalence of low-grade inflammation. Proteins involved in immune response and free radical scavenging were downregulated in the plasma of Luminal B patients, which is in agreement with defective immune system observed in cancer patients. These results reveal intrinsic subtype specific changes in the plasma proteome that may influence tumor progression as well as the systemic effects of cancer.     

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.     

Elucidation of the molecular mechanisms of preeclampsia using proteomic technologies

Preeclampsia, a disease of pregnancy, is a multisystem disorder associated with elevated maternal blood pressure, proteinurea, oedema, and fetal abnormalities. It is a major cause of mortality, morbidity, perinatal death, and premature delivery. Despite active research in the past decade, there is yet no definitive cure for preeclampsia. The disease has been treated symptomatically with antihypertensives, antieclamptics, bed rest, and a whole gamut of isolated therapies. In an attempt to understand the molecular basis of this disease and many other fatal diseases including cancer and heart disease, the scientific community has been turning to understanding the genome and more lately the "proteome". Proteomics enables researchers to identify all proteins expressed in a cell or organ and detect any PTM in the protein expression patterns. Deciphering the placental proteome and studying the differences in protein expression patterns in the normal as against the preeclamptic proteome might possibly in future lead to early detection and therapeutic targeting of preeclampsia.     

Clinical application of tear proteomics: Present and future prospects

Human tear fluid is charactered with very small volume and complex protein constitutes with a very large orders of magnitude. The tear proteome analysis provides a unique dataset (i.e., specific protein markers or protein patterns) that may be correlated to more effective diagnosis, prognosis, and response to therapy. Compared to less than 100 tear proteins obtained by the traditional methods, more than 400 proteins have been found in human tear fluid by current proteomic technologies. Many proteomics techniques, such as 2-DE, MALDI-TOF-MS, LC-MS, SELDI-TOF-MS, protein arrays, have been used to perform tear proteome analysis in healthy and/or disease subjects. The clinical application of tear proteomics needs suitable tear collection methods, standard tear handling procedures, and more sensitive and reliable proteomic technologies.     

Contribution of laser microdissection-based technology to proteomic analysis in hepatocellular carcinoma developing on cirrhosis

Hepatocellular carcinoma (HCC) is a major cause of cancer worldwide. Proteomic studies provide opportunities to uncover targets for the diagnosis and treatment of this disease. However, in HCC developing in a setting of cirrhosis, the detection of proteome alterations may be hampered by the increased cellular heterogeneity of tissue when analysing global liver homogenates. The aim of this study was to evaluate whether the identification of proteome alterations in these HCC cases was improved when the differential protein profile between tumour and non-tumour areas of liver was determined using hepatocytes isolated by laser microdissection (LM). Differential profiles established with LM-hepatocytes and liver section homogenates using 2-DE and MS exhibited noticeable differences: 30% of the protein spots with deregulated expression in tumorous LM-samples did not display any modification in homogenates; conversely 15% of proteins altered in tumorous homogenates were not impaired in LM-hepatocytes. These alterations resulted from the presence in cirrhotic liver of fibrotic stroma which displayed a protein pattern different from that determined in LM-hepatocytes. In conclusion, our data demonstrate the interest of LM in distinguishing between fibrotic and hepatocyte proteome alterations and thus the benefit of LM to proteome studies of HCC developing in a context of cirrhosis.     

Application of proteomics in the study of rodent models of cancer

The molecular and cellular mechanisms underlying the multistage processes of cancer progression and metastasis are complex and strictly depend on the interplay between tumor cells and surrounding tissues. Identification of protein aberrations in cancer pathophysiology requires a physiologically relevant experimental model. The mouse offers such a model to identify protein changes associated with tumor initiation and progression, metastasis development, tumor/microenvironment interplay, and treatment responses. Furthermore, the mouse model offers the ability to collect samples at any stage in tumor development from highly matched disease cases and controls with identical environmental and genetic backgrounds, thus providing an excellent method for biomarker discovery. Xenograft and genetically engineered mouse models have been widely used to identify proteomic patterns in tumor tissues and plasma samples associated with different stages of human cancer, including early cancer detection and development of metastasis. Here, we review proteomic strategies to identify proteins involved in key cancer processes within such animal models as well as biomarkers for diagnosis, prognosis, and monitoring of cancer progression and treatment response. Central to such studies is the ability to ensure at an early stage that the identified proteins are of clinical relevance by examining relevant specimens from larger cohorts of cancer patients.     

A catalogue of proteins released by colorectal cancer cells in vitro as an alternative source for biomarker discovery

Improved methods for the early diagnosis of colorectal cancer by way of sensitive and specific tumour markers are highly desirable. Therefore, efficient strategies for biomarker discovery are urgently needed. Here we present an approach that is based on the direct experimental access to proteins released by SW620 human colorectal cancer cells in vitro. A 2-D map and a catalogue of this subproteome - here termed the secretome - were established comprising more than 320 identified proteins which translate into approximately 220 distinct genes. As the majority of the secretome constituents were nominally cellular proteins, we directly compared the secretome and the total proteome by 2-D-DIGE analysis. We provide evidence that unspecific release through cell death, classical secretion, ectodomain shedding, and exosomal release contribute to the secretome in vitro, presumably reflecting the mechanisms in vivo which lead to the occurrence of tumour-specific proteins in the circulation. These data together with the fact that the SW620 secretome catalogue, as presented here, does comprise a large number of known and novel biomarker candidates, validates our approach to isolate and characterize the tumour cell secretome in vitro as a rich source for tumour biomarkers.     

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.     

Identification of nasopharyngeal carcinoma antigens that induce humoral immune response by proteomic analysis

A proteomics-based approach has been used to identify proteins that commonly elicit a humoral immune response in nasopharyngeal carcinoma (NPC). Sera from 19 newly diagnosed NPC patients and 19 healthy individuals were analyzed for IgG autoantibodies against NPC proteins resolved by 2-DE. Protein spots that exhibited selective reactivity with sera from NPC patients were identified by MS. Among nine identified proteins, cytokeratin 19 (CK19), Erb3 binding protein (EBP1), and Rho GDP dissociation inhibitor-beta (Rho-GDI-2) induced autoantibodies in more than 36.8% of NPC patients but not in healthy individuals. Furthermore, Western blot analysis and immunohistochemical staining were performed to determine the expression and localization of CK19, EBP1, and Rho-GDI-2 in NPC and normal nasopharyngeal mucosal tissues. Up-regulated CK19 and EBP1, but not Rho-GDI-2, were observed in NPC vs. normal tissue. Subcellular localization of the three proteins in NPC tissue was same as that in the normal tissue. Thus, overexpression of CK19 and EBP1 may be one of the mechanisms for their autoantibody development in NPC. To validate the findings of a proteomic analysis, occurrence of autoantibodies against these three proteins was detected by immunoprecipitation and Western blot analysis in additional 30 NPC patients, 23 other types of cancer patients and 20 healthy individuals. Results showed that frequency of autoantibodies against CK19, EBP1 and Rho-GDI-2 in NPC patients was significantly higher than that in other types of cancer patients and healthy individuals. We conclude that CK19, EBP1 and Rho-GDI-2 may have utility in NPC screening and diagnosis.