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.