Integrating intracellular and extracellular proteomic profiling for in-depth investigations of cellular communication in a model of prostate cancer

Cellular communication is essential for cell-cell interactions, maintaining homeostasis and progression of certain disease states. While many studies examine extracellular proteins, the holistic extracellular proteome is often left uncaptured, leaving gaps in our understanding of how all extracellular proteins may impact communication and interaction. We used a cellular-based proteomics approach to more holistically profile both the intracellular and extracellular proteome of prostate cancer. Our workflow was generated in such a manner that multiple experimental conditions can be observed with the opportunity for high throughput integration. Additionally, this workflow is not limited to a proteomic aspect, as metabolomic and lipidomic studies can be integrated for a multi-omics workflow. Our analysis showed coverage of over 8000 proteins while also garnering insights into cellular communication in the context of prostate cancer development and progression. Identified proteins covered a variety of cellular processes and pathways, allowing for the investigation of multiple aspects into cellular biology. This workflow demonstrates advantages for integrating intra- and extracellular proteomic analyses as well as potential for multi-omics researchers. This approach possesses great value for future investigations into the systems biology aspects of disease development and progression.     

Tissue and serum proteomic profiling for diagnostic and prognostic bladder cancer biomarkers

A panel of biomarkers for the early detection of bladder cancer has not yet been identified. Many different molecules, including DNA, RNA or proteins have been reported but none have provided adequate sensitivity for a single-tier screening test or a test to replace cystoscopy. Therefore, multimarker panels are discussed at present to give a more-precise answer to the biomarker quest. Mass spectrometry or 2D gel-electrophoresis have evolved greatly within recent years and are capable of analyzing multiple proteins or peptides in parallel with high sensitivity and specificity. However, transmission of screening results from one laboratory to another is still the main pitfall of those methods; a fact that emphasizes the need for consistent and standardized procedures as suggested by the Human Proteome Organization (HUPO). In this article, recent results in screening approaches and other proteomic techniques used for biomarker evaluation in bladder cancer are discussed with a focus on serum and tissue biomarkers.     

Detection of pancreatic cancer using antibody microarray-based serum protein profiling

The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.     

Quantitative proteomic profiling of pancreatic cancer juice

Pancreatic juice is an exceptionally rich source of cancer-specific proteins shed from cancerous ductal cells into the pancreatic juice. Quantitative proteomic analysis of the proteins specific to pancreatic cancer juice has not previously been reported. We used isotope-code affinity tag (ICAT) technology and MS/MS to perform quantitative protein profiling of pancreatic juice from pancreatic cancer patients and normal controls. ICAT technology coupled with MS/MS allows the systematic study of the proteome and measures the protein abundance in pancreatic juice with the potential for development of biomarkers. A total of 105 proteins were identified and quantified in the pancreatic juice from a pancreatic cancer patient, of which 30 proteins showed abundance changes of at least twofold in pancreatic cancer juice compared to normal controls. Many of these proteins have been externally validated. This is the first comprehensive study of the pancreatic juice proteome by quantitative global protein profiling, and the study reveals numerous proteins that are shown for the first time to be associated with pancreatic cancer, providing candidates for diagnostic biomarkers. One of the identified proteins, insulin-like growth factor binding protein-2 was further validated by Western blotting to be elevated in pancreatic cancer juice and overexpressed in pancreatic cancer tissue.     

Dendritic cells loaded with exosomes derived from cancer stem cell-enriched spheroids as a potential immunotherapeutic option

Cancer stem cells (CSCs) are responsible for therapeutic resistance and recurrence in colorectal cancer. Despite advances in immunotherapy, the inability to specifically eradicate CSCs has led to treatment failure. Hence, identification of appropriate antigen sources is a major challenge in designing dendritic cell (DC)-based therapeutic strategies against CSCs. Here, in an in vitro model using the HT-29 colon cancer cell line, we explored the efficacy of DCs loaded with exosomes derived from CSC-enriched colonospheres (CSC_enr-EXOs) as an antigen source in activating CSC-specific T-cell responses. HT-29 lysate, HT-29-EXOs and CSC_enr lysate were independently assessed as separate antigen sources. Having confirmed CSCs enrichment in spheroids, CSC_enr-EXOs were purified and characterized, and their impact on DC maturation was investigated. Finally, the impact of the antigen-pulsed DCs on the proliferation rate and also spheroid destructive capacity of autologous T cells was assessed. CSC_enr-EXOs similar to other antigen groups had no suppressive/negative impacts on phenotypic maturation of DCs as judged by the expression level of costimulatory molecules. Notably, similar to CSC_enr lysate, CSC_enr-EXOs significantly increased the IL-12/IL-10 ratio in supernatants of mature DCs. CSC_enr-EXO-loaded DCs effectively promoted T-cell proliferation. Importantly, T cells stimulated with CSC_enr-EXOs disrupted spheroids' structure. Thus, CSC_enr-EXOs present a novel and promising antigen source that in combination with conventional tumour bulk-derived antigens should be further explored in pre-clinical immunotherapeutic settings for the efficacy in hampering recurrence and metastatic spread.     

Carbonate extraction process for the metabolic, isozymic and proteomic profiling of rose-scented geranium (Pelargonium sp.), a hyper-acidic plant

Rose-scented geranium (Pelargonium sp.) is a valuable monoterpene-yielding plant. It has been well characterised phytochemically through the isolation of >270 secondary metabolites, however, there is hardly any biochemical or metabolic information concerning this plant. Initial attempts to investigate its metabolism failed to produce any enzyme activity in the tissue extracts prepared in routine extraction buffers owing to the intrinsic properties of the tissue matrix. It was recognised that cellular hyper-acidity (cell sap pH approximately 3.0) gave rise to very low protein levels in the extracts, thus prohibiting detection of activities of even primary metabolic enzymes that are usually abundantly present in plants. Tissue extraction in Tris solution without pH adjustment (as used for studies involving citrus and banana) led to little or no improvement. Therefore, a novel approach using sodium carbonate solution as an efficient extraction system for enzymes and proteins from the plant was studied. Functionality of the carbonate extraction has been demonstrated through its effectiveness, a several-fold superior performance, in yielding protein, monitoring primary metabolism and secondary metabolic enzymes, and isozymic and polypeptide profiling. The process may also be helpful in the reliable analysis of other acidic plant tissues.     

Evaluation on the effect of different in-gel peptide isoelectric focusing parameters in global proteomic profiling

Peptide isoelectric focusing (IEF) is a common technique used in two-dimensional liquid chromatography tandem mass spectrometry (2D–LC–MS/MS) proteomic workflow, in which the tryptic peptide is first pre-fractionated based on pI values before being subjected to reverse phase LC–MS analysis. Although this method has been widely used by many research groups, a systemic study on the optimal conditions and fundamental parameters influencing the experimental outcomes has been lacking, including the effect of peptide extraction methods, the extent of pre-fractionation, and the choice of pH range. In this study, we compared the effect of different parameters on the numbers of peptides and proteins identified using two complex mouse proteomes. The results indicated that extraction of peptides from immobilized pH gradient (IPG) strips by sequential elution of increasingly organic solvents provided the highest number of peptide identification. In addition, we showed that approximately 45 more unique proteins were identified for every additional fraction collected during peptide IEF. Although narrow pH ranges provided higher resolution in peptide separation as expected, different pH ranges yielded similar numbers of peptide and protein identification. Overall, we demonstrated that the extraction solvent influenced the numbers of peptide and protein identification and quantitatively demonstrated the advantage of extensive fractionation and the performance of different pH ranges in practice.     

Proteomic profiling of dextran sulfate sodium induced acute ulcerative colitis mice serum exosomes and their immunomodulatory impact on macrophages

Macrophages are essential for the maintenance of intestinal homeostasis, and their activation has been proposed to be critical to the pathogenesis of inflammatory bowel disease (IBD). Although there are many recognized mediators of macrophage activation, increasing evidence suggests that macrophages respond to exosome stimulation. Exosomes are 40–150 nm microvesicles released from different cell types and are found in a variety of physiological fluids, including serum. As studies have shown that circulating exosomes participate in intercellular communication and can mediate the immune response, we hypothesized that exosomes may play a role in the pathogenesis of IBD though modulation of macrophage activity. In this study, we used the dextran sulfate sodium (DSS) induced acute colitis mice model to investigate the effect of serum exosomes on macrophages and identify exosome proteins potentially involved in macrophage activation. We treated RAW264.7 macrophages with serum exosomes isolated from dextran sulfate sodium induced mice and found that treatment induced phosphorylation of p38 and ERK and production of tumor necrosis factor α when compared to treatment with exosomes isolated from control mice. Subsequent proteomic analysis identified 56 differentially expressed proteins, a majority of which were acute‐phase proteins and immunoglobulins. Bioinformatics analysis suggested these proteins were mainly involved in the complement and coagulation cascade, which has been implicated in macrophage activation. Our findings provide new insight into the role of circulating serum exosomes in acute colitis and contribute to the understanding of macrophage activation in the pathogenesis of IBD.     

Protein profiling of pancreatic islets

The insulin-producing β cell in the islet of Langerhans is central in glucose homeostasis. Its dysfunction is part of the pathogenesis of both Type 1 and 2 diabetes mellitus. In both forms of the disease, there is a cytotoxic component either induced by cytokines, as in Type 1 diabetes, or by elevated levels of glucose and fatty acids, as in Type 2 diabetes. To find the mechanisms responsible for the cytotoxic effects of these compounds proteomic approaches with 2D gel electrophoresis and surface-enhanced laser desorption/ionization time-of-flight mass spectrometry have been undertaken. In this article, we describe these methods, and other methodological aspects of protein profiling of pancreatic islets, and summarize the results obtained with these methods.     

Glycosylation of serum ribonuclease 1 indicates a major endothelial origin and reveals an increase in core fucosylation in pancreatic cancer

Human pancreatic ribonuclease 1 (RNase 1) is a glycoprotein expressed mainly by the pancreas and also found in endothelial cells. The diagnosis of pancreatic cancer (PaC) remains difficult and therefore the search for sensitive and specific markers is required. Previous studies showed that RNase 1 from human healthy pancreas contained only neutral glycans, whereas RNase 1 from PaC cell lines contained sialylated structures. To determine whether these glycan tumor cell-associated changes were also characteristic of serum RNase 1 and could be used as a marker of PaC, we have analyzed the glycosylation of serum RNase 1. The origin of serum RNase 1 was also investigated. Serum RNase 1 from two PaC patients and two controls was purified and the glycans analyzed by high-performance liquid chromatography (HPLC)-based sequencing and mass spectrometry. Although normal and tumor serum RNase 1 contained the same glycan structures, there was an increase of 40% in core fucosylation in the main sialylated biantennary glycans in the PaC serum RNase 1. This change in proportion would be indicative of a subset of tumor-associated glycoforms of RNase 1, which may provide a biomarker for PaC. Two-dimensional electrophoresis of the RNase 1 from several endothelial cell lines, EA.hy926, human umbilical vein endothelial cells (HUVEC), human mammary microvessel endothelial cells (HuMMEC), and human lung microvessel endothelial cells (HuLEC), showed basically the same pattern and was also very similar to that of serum RNase 1. RNase 1 from EA.hy926 was then purified and presented a glycosylation profile very similar to that from serum RNase 1, suggesting that endothelial cells are the main source of this enzyme.     

Implications of exosomes as diagnostic and therapeutic strategies in cancer

Exosomes offer a new perspective on the biology of cancer with both diagnostic and therapeutic concepts. Due to the cell-to-cell association, exosomes are involved in the progression, metastasis, and therapeutic efficacy of the tumor. They can be isolated from blood and other body fluids to determine the disease progression in the body, including cancer growth. In addition to being reservoirs of biochemical markers of cancer, exomes can be designed to restore tumor immunity. Tumor exosomes interact with different cells in the tumor microenvironment to confer beneficial modulations, responsible for stromal activity, angiogenesis, increased vascular permeability, and immune evasion. Exosomes also contribute to the metastasis with the aim of epithelial transmission to the mesenchyme and the formation of premetastatic niches. Moreover, exosomes protect cells against the cytotoxic effects of chemotherapeutic drugs and prevent the transmission of chemotherapy resistance to adjacent cells. Therefore, exosomes are essential for many fatal cancer agents, and understanding their origins and role in cancer is important. In this article, we attempted to clarify the potential of exosomes for the application in cancer diagnosis and therapy.     

Comparative proteomic analysis of human pancreatic juice: methodological study

Pancreatic cancer is the most lethal of all the common malignancies. Markers for early detection of this disease are urgently needed. Here, we optimized and applied a proteome analysis of human pancreatic juice to identify biomarkers for pancreatic cancer. Pancreatic juice samples, devoid of blood or bile contamination, were collected from patients with pancreatic cancer (n = 5), benign pancreatic diseases (n = 6), or cholelithiasis (n = 3) during endoscopic retrograde cholangiopancreatography (ERCP). After ultramembrane centrifugation sample preparation, pancreatic juice proteins were separated by 2-DE and identified by MALDI-TOF-MS. A 2-DE dataset of pancreatic juice from patients with cholelithiasis was established, consisting of 76 protein spots representing 22 different proteins. Disease-associated obstruction of the pancreatic duct strongly effected the protein composition of pancreatic juice. Concurrently, pancreatic juice from patients with pancreatic cancer was compared to nonmalignant controls with comparable obstruction of pancreatic ducts. Seven protein spots were identified that consistently appeared at changed levels in pancreatic juice from patients with pancreatic cancer. In conclusion, comparative proteomic analysis of human pancreatic juice can be used to identify biomarkers of pancreatic cancer.     

Methylation profiling identified novel differentially methylated markers including OPCML and FLRT2 in prostate cancer

To develop new methods to distinguish indolent from aggressive prostate cancers (PCa), we utilized comprehensive high-throughput array-based relative methylation (CHARM) assay to identify differentially methylated regions (DMRs) throughout the genome, including both CpG island (CGI) and non-CGI regions in PCa patients based on Gleason grade. Initially, 26 samples, including 8 each of low [Gleason score (GS) 6] and high (GS ≥7) grade PCa samples and 10 matched normal prostate tissues, were analyzed as a discovery cohort. We identified 3,567 DMRs between normal and cancer tissues, and 913 DMRs distinguishing low from high-grade cancers. Most of these DMRs were located at CGI shores. The top 5 candidate DMRs from the low vs. high Gleason comparison, including OPCML, ELAVL2, EXT1, IRX5, and FLRT2, were validated by pyrosequencing using the discovery cohort. OPCML and FLRT2 were further validated in an independent cohort consisting of 20 low-Gleason and 33 high-Gleason tissues. We then compared patients with biochemical recurrence (n=70) vs. those without (n=86) in a third cohort, and they showed no difference in methylation at these DMR loci. When GS 3+4 cases and GS 4+3 cases were compared, OPCML-DMR methylation showed a trend of lower methylation in the recurrence group (n=30) than in the no-recurrence (n=52) group. We conclude that whole-genome methylation profiling with CHARM revealed distinct patterns of differential DNA methylation between normal prostate and PCa tissues, as well as between different risk groups of PCa as defined by Gleason scores. A panel of selected DMRs may serve as novel surrogate biomarkers for Gleason score in PCa.     

Quantitative profiling of serum samples using TMT protein labelling, fractionation and LC-MS/MS

Blood-borne biomarkers are urgently required for the early detection, accurate diagnosis and prognosis of disease. Additionally, improved methods of profiling serum and plasma proteins for biomarker discovery efforts are needed. Herein, we report a quantitative method based on amino-group labelling of serum proteins (rather than peptides) with isobaric tandem mass tags (TMT) and incorporating immune-based depletion, gel-based and strong anion exchange separation of proteins prior to differential endoproteinase treatment and liquid chromatography tandem mass spectrometry. We report a generally higher level of quantitative coverage of the serum proteome compared to other peptide-based isobaric tagging approaches and show the potential of the method by applying it to a set of unique samples that pre-date the diagnosis of pancreatic cancer.     

LC-MS-based serum metabolic profiling for genitourinary cancer classification and cancer type-specific biomarker discovery

Bladder cancer (BC) and kidney cancer (KC) are the first two commonly occurring genitourinary cancers in China. In this study, a comprehensive LC-MS-based method, which utilizes both reversed phase liquid chromatography (RPLC) and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of BC, KC, and noncancer controls. An independent test set consisting of different patients has been used to objectively evaluate the predictive ability of the analysis platform. Excellent sensitivity and specificity have been achieved in detection of KC and BC. The results suggest that serum metabolic profiling could be used for different types of genitourinary cancer diagnosis. Furthermore, cancer type-specific biomarkers were found through a critical selection criterion. As a result, eicosatrienol, azaprostanoic acid, docosatrienol, retinol, and 14'-apo-beta-carotenal were found as specific biomarkers for BC; and PE(P-16:0e/0:0), glycerophosphorylcholine, ganglioside GM3 (d18:1/22:1), C17 sphinganine, and SM(d18:0/16:1(9Z)) were found as specific biomarkers for KC. Receiver operating characteristic (ROC) analysis was used for the preliminary evaluation of the biomarkers. These biomarkers have great potential to be used in the clinical diagnosis after further rigorous assessment.     

Serum proteome profiling for diagnostics of ovarian cancer using ClinProt magnetic technique and MALDI-TOF mass spectrometry

Using ClinProt magnetic beads with reverse-phase (MB-HIC 8 and HB-HIC 18), weak cation exchange (MB-WCX) and metal affinity (MB-IMAC Cu) surfaces fractions of peptides and proteins were isolated from human sera for their profiling by MALDI-TOF mass spectrometry. Proteome profiling of sera from basically healthy women (47 subjects, average age 49) and from women with verified ovarian cancer (stages 1-IV, 47 patients, average age 51) by means of MB-WCX beads allowed to generate the best diagnostic models based on Genetic Algorithm and Supervised Neural Network classifiers; these models demonstrated 100% sensitivity and specificity during analysis of the test set. Introduction of additional sera from patients with colorectal cancer (19) and ulcerous colitis (5) to the statistical model confirmed 100% ovarian cancer recognition. Statistical analysis of mass-spectrometry peak areas included to the diagnostic classifiers showed 3 peaks characteristic for ovarian cancer and 4 peak areas exhibiting changes associated with both ovarian and colorectal cancer.