Proteomic technologies and their application to pancreatic cancer

A Quantitative Global Proteomics Approach Identifies Candidate Urinary Biomarkers That Correlate With Intraductal Papillary Mucinous Neoplasm Dysplasia

OBJECTIVES

A proteomic discovery study was performed to determine if urine possesses a unique biosignature that could form the basis for a noninvasive test able to predict intraductal papillary mucinous neoplasm (IPMN) dysplasia.

METHODS

Urine was collected from patients undergoing surgery for IPMN (72 low/moderate, 27 high-grade/invasive). Quantitative mass spectrometry-based proteomics was performed. Proteins of interest were identified by differential expression analysis followed by principal component analysis.

RESULTS

Proteomics identified greater than 4800 urinary proteins. Low/moderate and high-grade/invasive IPMN were distinguished by 188 proteins (P < 0.05). Following principal component analysis and heatmap visualization, vitamin D binding protein (DBP), apolipoprotein A1 (APOA1), and alpha-1 antitrypsin (A1AT) were selected. The proteomic abundance of DBP (median [interquartile range]) was significantly higher for high-grade/invasive than for low/moderate IPMN (219,735 [128,882-269,943] vs. 112,295 [77,905-180,773] normalized reporter ion intensity units; P = 0.001). Similarly, APOA1 was more abundant in the high-grade/invasive than low/moderate groups (235,420 [144,933-371,247] vs 150,095 [103,419-236,591]; P = 0.0007) as was A1AT (567,514 [358,544-774,801] vs 358,393 [260,850-477,882]; P = 0.0006).

CONCLUSIONS

Urinary DBP, APOA1, and A1AT represent potential biomarker candidates that may provide a noninvasive means of predicting IPMN dysplastic grade.

Proteomic analysis of docetaxel resistance in human nasopharyngeal carcinoma cells using the two-dimensional gel electrophoresis method

Docetaxel-based chemotherapy has been recommended for advanced nasopharyngeal carcinoma (NPC). However, treatment failure often occurs because of acquired drug resistance. In this study, a docetaxel-resistant NPC cell line CNE-2R was established with increasing doses of docetaxel for more than 6 months. Two-dimensional gel electrophoresis and ESI-Q-TOF-MS were used to compare the differential expression of docetaxel-resistance-associated proteins between human NPC CNE-2 cells and docetaxel-resistant CNE-2R cells. As a result, 24 differentially expressed proteins were identified, including 11 proteins with increased expression and 13 proteins with decreased expression. These proteins function in diverse biological processes such as metabolism, signal transduction, calcium ion binding, immune response, proteolysis, and so on. Among these, α-enolase (ENO1), significantly upregulated in CNE-2R, was selected for detailed analysis. Inhibition of ENO1 by shRNA restored CNE-2R cells' sensitivity to docetaxel. Moreover, overexpression of ENO1 could facilitate the development of acquired resistance of docetaxel in CNE-2 cells. Western blot and reverse-transcription PCR data of clinical samples confirmed that α-enolase was upregulated in docetaxel-resistant human NPC tissues. Finding such proteins might improve interpretation of the molecular mechanisms leading to the acquisition of docetaxel chemoresistance.

Glycoproteins and glycoproteomics in pancreatic cancer

Aberrations in protein glycosylation and polysaccharides play a pivotal role in pancreatic tumorigenesis, influencing cancer progression, metastasis, immuno-response and chemoresistance. Abnormal expression in sugar moieties can impact the function of various glycoproteins, including mucins, surface receptors, adhesive proteins, proteoglycans, as well as their effectors and binding ligands, resulting in an increase in pancreatic cancer invasiveness and a cancer-favored microenvironment. Recent advance in glycoproteomics, glycomics and other chemical biology techniques have been employed to better understand the complex mechanism of glycosylation events and how they orchestrate molecular activities in genomics, proteomics and metabolomics implicated in pancreatic adenocarcinoma. A variety of strategies have been demonstrated targeting protein glycosylation and polysaccharides for diagnostic and therapeutic development.

Establishment of a decision tree model for diagnosis of early rheumatoid arthritis by proteomic fingerprinting

AIM

The objective of this study was to identify proteomic biomarkers specific for rheumatoid arthritis (RA) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in combination with weak cationic exchange (WCX) magnetic beads.

METHODS

Serum samples from 50 patients with RA and 110 disease controls (50 SLE and 60 SS) and 51 healthy individuals were analyzed. The samples were randomly divided into a training set or test set to develop a diagnostic model for RA.

RESULTS

A total of 83 protein peaks were identified to be related with RA, in which four of the peaks with mass-charge ratio (m/z) at 8133.85, 5844.60, 13 541.3 and 14 029.0 were selected to establish a model for diagnosis of RA. This classification model could separate patients with RA from diseased and healthy controls with sensitivity of 84.0% and specificity of 92.5%, and its accuracy was confirmed in the blind testing set with high sensitivity and specificity of 80.0% and 93.3%, respectively.

CONCLUSIONS

This study suggested that potential serum biomarkers for RA diagnosis could be discovered by MALDI-TOF-MS. The classification tree model set up in this study might be used as a novel diagnostic tool for RA.

Proteomics analysis of bodily fluids in pancreatic cancer

Proteomics study of pancreatic cancer using bodily fluids emphasizes biomarker discovery and clinical application, presenting unique prospect and challenges. Depending on the physiological nature of the bodily fluid and its proximity to pancreatic cancer, the proteomes of bodily fluids, such as pancreatic juice, pancreatic cyst fluid, blood, bile, and urine, can be substantially different in terms of protein constitution and the dynamic range of protein concentration. Thus, a comprehensive discovery and specific detection of cancer-associated proteins within these varied fluids is a complex task, requiring rigorous experiment design and a concerted approach. While major challenges still remain, fluid proteomics studies in pancreatic cancer to date have provided a wealth of information in revealing proteome alterations associated with pancreatic cancer in various bodily fluids.

Immunoassay-based proteome profiling of 24 pancreatic cancer cell lines

Pancreatic ductal adenocarcinoma is one of the most deadly forms of cancers, with a mortality that is almost identical to incidence. The inability to predict, detect or diagnose the disease early and its resistance to all current treatment modalities but surgery are the prime challenges to changing the devastating prognosis. Also, relatively little is known about pancreatic carcinogenesis. In order to better understand relevant aspects of pathophysiology, differentiation, and transformation, we analysed the cellular proteomes of 24 pancreatic cancer cell lines and two controls using an antibody microarray that targets 741 cancer-related proteins. In this analysis, 72 distinct disease marker proteins were identified that had not been described before. Additionally, categorizing cancer cells in accordance to their original location (primary tumour, liver metastases, or ascites) was made possible. A comparison of the cells' degree of differentiation (well, moderately, or poorly differentiated) resulted in unique marker sets of high relevance. Last, 187 proteins were differentially expressed in primary versus metastatic cancer cells, of which the majority is functionally related to cellular movement.

Proteomics portrait of archival lesions of chronic pancreatitis

Chronic pancreatitis is a chronic inflammatory disorder of the pancreas. The etiology is multi-fold, but all lead to progressive scarring and loss of pancreatic function. Early diagnosis is difficult; and the understanding of the molecular events that underlie this progressive disease is limited. In this study, we investigated differential proteins associated with mild and severe chronic pancreatitis in comparison with normal pancreas and pancreatic cancer. Paraffin-embedded formalin-fixed tissues from five well-characterized specimens each of normal pancreas (NL), mild chronic pancreatitis (MCP), severe chronic pancreatitis (SCP) and pancreatic ductal adenocarcinoma (PDAC) were subjected to proteomic analysis using a “label-free” comparative approach. Our results show that the numbers of differential proteins increase substantially with the disease severity, from mild to severe chronic pancreatitis, while the number of dysregulated proteins is highest in pancreatic adenocarcinoma. Important functional groups and biological processes associated with chronic pancreatitis and cancer include acinar cell secretory proteins, pancreatic fibrosis/stellate cell activation, glycoproteins, and inflammatory proteins. Three differential proteins were selected for verification by immunohistochemistry, including collagen 14A1, lumican and versican. Further canonical pathway analysis revealed that acute phase response signal, prothrombin activation pathway, and pancreatic fibrosis/pancreatic stellate cell activation pathway were the most significant pathways involved in chronic pancreatitis, while pathways relating to metabolism were the most significant pathways in pancreatic adenocarcinoma. Our study reveals a group of differentially expressed proteins and the related pathways that may shed light on the pathogenesis of chronic pancreatitis and the common molecular events associated with chronic pancreatitis and pancreatic adenocarcinoma.

Comparative proteomic approach identifies PKM2 and cofilin-1 as potential diagnostic, prognostic and therapeutic targets for pulmonary adenocarcinoma

Lung cancer is the leading cause of cancer-related death in the world. Non-small cell lung carcinomas (Non-SCLC) account for almost 80% of lung cancers, of which 40% were adenocarcinomas. For a better understanding of the molecular mechanisms behind the development and progression of lung cancer, particularly lung adenocarcinoma, we have used proteomics technology to search for candidate prognostic and therapeutic targets in pulmonary adenocarcinoma. The protein profile changes between human pulmonary adenocarcinoma tissue and paired surrounding normal tissue were analyzed using two-dimensional polyacrylamide gel electrophoresis (2-DE) based approach. Differentially expressed protein-spots were identified with ESI-Q-TOF MS/MS instruments. As a result, thirty two differentially expressed proteins (over 2-fold, p<0.05) were identified in pulmonary adenocarcinoma compared to normal tissues. Among them, two proteins (PKM2 and cofilin-1), significantly up-regulated in adenocarcinoma, were selected for detailed analysis. Immunohistochemical examination indicated that enhanced expression of PKM2 and cofilin-1 were correlated with the severity of epithelial dysplasia, as well as a relatively poor prognosis. Knockdown of PKM2 expression by RNA interference led to a significant suppression of cell growth and induction of apoptosis in pulmonary adenocarcinoma SPC-A1 cells in vitro, and tumor growth inhibition in vivo xenograft model (P<0.05). In addition, the shRNA expressing plasmid targeting cofilin-1 significantly inhibited tumor metastases and prolonged survival in LL/2 metastatic model. While additional works are needed to elucidate the biological significance and molecular mechanisms of these altered proteins identified in this study, PKM2 and cofilin-1 may serve as potential diagnostic and prognostic biomarkers, as well as therapeutic targets for pulmonary adenocarcinoma.

A multiplexed bead assay for profiling glycosylation patterns on serum protein biomarkers of pancreatic cancer

A multiplexed bead-based immunoassay was developed to simultaneously profile glycosylation patterns of serum proteins to investigate their usefulness as biomarkers for pancreatic cancer. The multiplex assay utilized protein-specific capture antibodies chemically coupled individually to beads labeled with specific amounts of fluorescent dye. Captured proteins were detected based on the extent and specific type of glycosylation as determined by successive binding of fluorescent lectin probes. Advantages to this technique include the fact that antibodies coupled to the beads had minimal nonspecific binding to the lectins ConA/SNA, avoiding the step of chemically blocking the antibody glycans and the bead assays were performed in a 96-well filter plate enabling high-throughput screening applications with improved reproducibility. The assay was tested with ConA and SNA lectins to examine the glycosylation patterns of α-1-β glycoprotein (A1BG) and serum amyloid p (SAP) component for use as potential biomarkers for the detection of pancreatic cancer based on the results from prior biomarker studies. The results showed that the SNA response on the captured A1BG protein could distinguish chronic pancreatitis samples from pancreatic cancer with a p-value of 0.035 and for the SAP protein with SNA, a p-value of 0.026 was found between the signal of normal controls and the pancreatic cancer samples. For the ConA response, a decline in the signal for both proteins in the serum samples was found to distinguish pancreatic cancer from normal controls and renal cell carnoma samples (A1BG, p<0.05; and SAP, p<0.0001).

Protein alterations associated with pancreatic cancer and chronic pancreatitis found in human plasma using global quantitative proteomics profiling

Pancreatic cancer is a lethal disease that is difficult to diagnose at early stages when curable treatments are effective. Biomarkers that can improve current pancreatic cancer detection would have great value in improving patient management and survival rate. A large scale quantitative proteomics study was performed to search for the plasma protein alterations associated with pancreatic cancer. The enormous complexity of the plasma proteome and the vast dynamic range of protein concentration therein present major challenges for quantitative global profiling of plasma. To address these challenges, multidimensional fractionation at both protein and peptide levels was applied to enhance the depth of proteomics analysis. Employing stringent criteria, more than 1300 proteins total were identified in plasma across 8-orders of magnitude in protein concentration. Differential proteins associated with pancreatic cancer were identified, and their relationship with the proteome of pancreatic tissue and pancreatic juice from our previous studies was discussed. A subgroup of differentially expressed proteins was selected for biomarker testing using an independent cohort of plasma and serum samples from well-diagnosed patients with pancreatic cancer, chronic pancreatitis, and nonpancreatic disease controls. Using ELISA methodology, the performance of each of these protein candidates was benchmarked against CA19-9, the current gold standard for a pancreatic cancer blood test. A composite marker of TIMP1 and ICAM1 demonstrate significantly better performance than CA19-9 in distinguishing pancreatic cancer from the nonpancreatic disease controls and chronic pancreatitis controls. In addition, protein AZGP1 was identified as a biomarker candidate for chronic pancreatitis. The discovery and technical challenges associated with plasma-based quantitative proteomics are discussed and may benefit the development of plasma proteomics technology in general. The protein candidates identified in this study provide a biomarker candidate pool for future investigations.

A proteomic investigation into adriamycin chemo-resistance of human leukemia K562 cells

This study aimed to explore the mechanism of adriamycin resistance in human chronic myelogenous leukemia cells. Proteomic approach was utilized to compare and identify differentially expressed proteins between human chronic myelogenous leukemia K562 cells and their adriamycin-resistant counterparts. The differentially expressed proteins were analyzed by 2-DE (two-dimensional gel electrophoresis), and protein identification were performed on ESI-Q-TOF MS/MS instrument. Out of the 35 differentially expressed proteins between the two cell lines, 29 were identified and grouped into 10 functional classes. Most of identified proteins were related to the categories of metabolism (24%), proteolysis (13%), signal transduction (21%) and calcium ion binding (6%), suggesting that alterations of those biological processes might be involved in adriamycin resistance of K562 cells. We believe this study may provide some clues to a better understanding of the molecular mechanisms underlying adriamycin resistance.

Proteome analysis of human pancreatic cancer cell lines with highly liver metastatic potential by antibody microarray

Antibody microarrays have been successfully used to determine relative abundance of key proteins in various cancers and other diseases. We have previously showed liver metastatic-related genes between the metastatic pancreatic cancer line (SW1990HM) and its parental line (SW1990). In this study, we searched for potential markers for metastatic progression using antibody microarrays. The SpringBio Antibody Microarrays were used to analysis the different proteomes between SW1990HM and SW1990 cells. A standard ≥2.0-fold cutoff value was used to determine differentially expressed proteins and Western blotting analysis further confirmed the results. Antibody microarrays revealed that 40 proteins were reproducibly altered more than 2-fold between the selected variant and its parental counterpart; 14 of the proteins were up-regulated, and 26 were down-regulated. Most of the up-regulated proteins (7/14) play a role in tumor signal transduction, while a number of down-regulated proteins (10/26) function in cell differentiation; this might be crucial for pancreatic cancer metastasis. Four dysregulated proteins were validated by western blotting in the cell lines. Interestingly, the up-regulation of Glucagon and down-regulation of Prolactin were further confirmed in the culture supernatants by western blotting. These proteomic data are valuable for understanding pancreatic cancer metastasis and searching for potential markers of metastatic progression.

Conventional and Proteomic Technologies for the Detection of Early Stage Malignancies: Markers for Ovarian Cancer

Our understanding of the tumor microenvironment continues to evolve and allows for the identification of biomarkers that should detect the presence of early stage malignancies. Recent advances in computational analysis and biomedical technologies have come together to elucidate signatures associated with cancer and that are capable of identifying unique tumor-specific proteins. Within the tumor microenvironment, we continue to characterize the proteophysiology of the different steps associated with tumor progression. The urgent need for biomarkers accurately detecting early-stage epithelial ovarian cancer has prompted us, and others, to engage in a search for specific peptide signatures that may discriminate transformed cells from those of the normal ovarian microenvironment. This endeavor also provides new insights into the biology of the disease, which may not only be applicable to detection but may also help to initiate new therapies and optimize patient care.

Proteome analysis of human pancreatic ductal adenocarcinoma tissue using two-dimensional gel electrophoresis and tandem mass spectrometry for identification of disease-related proteins

A comparative proteomic approach has been used to identify and analyze proteins related to pancreatic cancer. Proteomes of eight pairs of clinical pancreatic ductal adenocarcinoma (PDAC) tissue samples and samples of normal adjacent tissue were obtained by two-dimensional gel electrophoresis (2DE). Comprehensive analysis of proteins was focused on total protein spots for which there were statistical differences between the two groups. Proteins were identified by peptide mass fingerprinting with tandem mass spectrometry (MS-MS). Western blotting and immunohistochemistry (IHC) were also performed to verify the expression of some candidate proteins. Thirty protein spots were identified, including proteases, antioxidant proteins, signal-transduction proteins, calcium-binding proteins, structural proteins, chaperones, and others. Western blotting and IHC confirmed up-regulated expression of two candidate proteins, nucleotide diphosphatase kinase (NDPK) and annexin II, in tumorous tissues. These results suggest that combination of 2DE with MS is an effective strategy for discovery of differently expressed proteins in PDAC which may be molecular markers for diagnosis or therapeutic targets.

Proteomics in cancer research: Methods and application of array-based protein profiling technologies

With the human genome sequence now determined, the field of molecular medicine is moving beyond genomics to proteomics, the large-scale analysis of proteins. It is now possible to examine the expression of more than 1000 proteins using mass spectrometry technology coupled with various separation methods. Microarray technology is a new and efficient approach, for extracting relevant biomedical data and has a wide range of applications. It provides a versatile tool to study protein-protein, protein-nucleic acid, protein-lipid, enzyme-substrate and protein-drug interactions. This review paper will explore the key themes in proteomics and their application in clinical cancer research.