Analysis of the urine proteome in patients with pancreatic ductal adenocarcinoma

Identification of a urinary CD276 fragment for detecting resectable pancreatic cancer using a C-terminal proteomics strategy

This study aimed to confirm urinary protein fragments in relation to the presence of pancreatic ductal adenocarcinoma (PDAC) via a C-terminal proteomics strategy using exploratory and validation cohorts. Urinary fragments were examined by iTRAQ-labelling of tryptic peptides and concentrations of C-terminal fragments were evaluated. Only the urinary CD276 fragment showed a fold change (FC) of > 1.5 with a significant difference of P < 0.01 between healthy (H) and PDAC participants in both the exploratory (H, n = 42; PDAC, n = 39) and validation cohorts (H, n = 36; resectable PDAC, n = 28). The sensitivity and specificity of the CD276 fragment for diagnosing resectable PDAC were 75% and 89%, respectively, in the validation cohort. Postoperative urinary levels of the CD276 fragment were low as compared to those before surgery (n = 18, P < 0.01). Comprehensive C-terminus proteomics identified an increase in the urinary CD276 fragment level as a feature of patients with PDAC. The urinary CD276 fragment is a potential biomarker for detecting resectable PDAC.

Protein Biomarker Discovery Studies on Urinary sEV Fractions Separated with UF-SEC for the First Diagnosis and Detection of Recurrence in Bladder Cancer Patients

Urinary extracellular vesicles (EVs) are an attractive source of bladder cancer biomarkers. Here, a protein biomarker discovery study was performed on the protein content of small urinary EVs (sEVs) to identify possible biomarkers for the primary diagnosis and recurrence of non-muscle-invasive bladder cancer (NMIBC). The sEVs were isolated by ultrafiltration (UF) in combination with size-exclusion chromatography (SEC). The first part of the study compared healthy individuals with NMIBC patients with a primary diagnosis. The second part compared tumor-free patients with patients with a recurrent NMIBC diagnosis. The separated sEVs were in the size range of 40 to 200 nm. Based on manually curated high quality mass spectrometry (MS) data, the statistical analysis revealed 69 proteins that were differentially expressed in these sEV fractions of patients with a first bladder cancer tumor vs. an age- and gender-matched healthy control group. When the discriminating power between healthy individuals and first diagnosis patients is taken into account, the biomarkers with the most potential are MASP2, C3, A2M, CHMP2A and NHE-RF1. Additionally, two proteins (HBB and HBA1) were differentially expressed between bladder cancer patients with a recurrent diagnosis vs. tumor-free samples of bladder cancer patients, but their biological relevance is very limited.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

The next "sweet" spot for pancreatic ductal adenocarcinoma: Glycoprotein for early detection

Pancreatic ductal adenocarcinoma (PDAC) is the most common neoplastic disease of the pancreas, accounting for more than 90% of all pancreatic malignancies. As a highly lethal malignancy, PDAC is the fourth leading cause of cancer-related deaths worldwide with a 5-year overall survival of less than 8%. The efficacy and outcome of PDAC treatment largely depend on the stage of disease at the time of diagnosis. Surgical resection followed by adjuvant chemotherapy remains the only possibly curative therapy, yet 80%-90% of PDAC patients present with nonresectable PDAC stages at the time of clinical presentation. Despite our advancing knowledge of PDAC, the prognosis remains strikingly poor, which is primarily due to the difficulty of diagnosing PDAC at the early stages. Recent advances in glycoproteomics and glycomics based on mass spectrometry have shown that aberrations in protein glycosylation plays a critical role in carcinogenesis, tumor progression, metastasis, chemoresistance, and immuno-response of PDAC and other types of cancers. A growing interest has thus been placed upon protein glycosylation as a potential early detection biomarker for PDAC. We herein take stock of the advancements in the early detection of PDAC that were carried out with mass spectrometry, with special focus on protein glycosylation.

A novel nomogram model combining CT texture features and urine energy metabolism to differentiate single benign from malignant pulmonary nodule

Objective

To investigate a novel diagnostic model for benign and malignant pulmonary nodule diagnosis based on radiomic and clinical features, including urine energy metabolism index.

Methods

A total of 107 pulmonary nodules were prospectively recruited and pathologically confirmed as malignant in 86 cases and benign in 21 cases. A chest CT scan and urine energy metabolism test were performed in all cases. A nomogram model was established in combination with radiomic and clinical features, including urine energy metabolism levels. The nomogram model was compared with the radiomic model and the clinical feature model alone to test its diagnostic validity, and receiver operating characteristic (ROC) curves were plotted to assess diagnostic validity.

Results

The nomogram was established using a logistic regression algorithm to combine radiomic features and clinical characteristics including urine energy metabolism results. The predictive performance of the nomogram was evaluated using the area under the ROC and calibration curve, which showed the best performance, area under the curve (AUC) = 0.982, 95% CI = 0.940-1.000, compared to clinical and radiomic models in the testing cohort. The clinical benefit of the model was assessed using the decision curve analysis (DCA) and using the nomogram for benign and malignant pulmonary nodules, and preoperative prediction of benign and malignant pulmonary nodules using nomograms showed better clinical benefit.

Conclusion

This study shows that a coupled model combining CT imaging features and clinical features (including urine energy metabolism) in combination with the nomogram model has higher diagnostic performance than the radiomic and clinical models alone, suggesting that the combination of both methods is more advantageous in identifying benign and malignant pulmonary nodules.

Biomarkers in the diagnosis of pancreatic cancer: Are we closer to finding the golden ticket?

Pancreatic cancer (PC) is a leading cause of cancer related mortality on a global scale. The disease itself is associated with a dismal prognosis, partly due to its silent nature resulting in patients presenting with advanced disease at the time of diagnosis. To combat this, there has been an explosion in the last decade of potential candidate biomarkers in the research setting in the hope that a diagnostic biomarker may provide a glimmer of hope in what is otherwise quite a substantial clinical dilemma. Currently, serum carbohydrate antigen 19-9 is utilized in the diagnostic work-up of patients diagnosed with PC however this biomarker lacks the sensitivity and specificity associated with a gold-standard marker. In the search for a biomarker that is both sensitive and specific for the diagnosis of PC, there has been a paradigm shift towards a focus on liquid biopsy and the use of diagnostic panels which has subsequently proved to have efficacy in the diagnosis of PC. Currently, promising developments in the field of early detection on PC using diagnostic biomarkers include the detection of microRNA (miRNA) in serum and circulating tumour cells. Both these modalities, although in their infancy and yet to be widely accepted into routine clinical practice, possess merit in the early detection of PC. We reviewed over 300 biomarkers with the aim to provide an in-depth summary of the current state-of-play regarding diagnostic biomarkers in PC (serum, urinary, salivary, faecal, pancreatic juice and biliary fluid).

Association between aberrant dynein cytoplasmic 1 light intermediate chain 1 expression levels, mucins and chemosensitivity in colorectal cancer

Dynein transport along the cytoskeletal microtubules towards the minus end is essential for cell division, cell migration and other basic cellular functions. Dynein cytoplasmic 1 light intermediate chain 1 (DYNC1LI1) has been previously associated with pancreatic ductal adenocarcinoma, hepatocellular carcinoma and prostate cancer. Cytoskeletal structures are involved in the regulation of the mucosal barrier integrity. Thus, improving our understanding of the molecular mechanisms that regulate the mucosal barrier is critical for cancer management and treatment. The present study aimed to investigate DYNC1LI1 expression in colorectal cancer (CRC) tissues. The American Joint Committee on Cancer Stage II CRC cell line LS 174T was used to determine the association between the cellular expression levels of DYNC1LI1 and different types of mucin (MUC) by reverse transcription-quantitative PCR. The role of DYNC1LI1 in cell chemosensitivity and proliferation was also evaluated in the presence of the DNA analog 5-fluorouracil (5-FU) or the platinum-based drug, oxaliplatin by the MTT assay. LS 174T cells with decreased expression levels of DYNC1LI1 were discovered to be more sensitive to 5-FU compared with LS 174T cells with endogenous DYNC1LI1 expression levels. Moreover, LS 174T cells transfected with short hairpin RNA targeting DYNC1LI1 were associated with low MUC1 and high MUC2, MUC4 and MUC5AC expression levels. Notably, the CRC cells with low MUC1 expression levels and high expression levels of the other MUCs (MUC2, MU4 and MUC5AC) were shown to benefit from 5-FU treatment. In conclusion, the findings of the present study have suggested that DYNC1LI1 expression may be significantly associated with MUC expression levels and may be used to predict the chemotherapeutic efficiency. However, additional functional studies and clinical reports are required for an improved understanding of the significance of these molecular interactions in tumorigenesis.

An Integrated Meta-Analysis of Secretome and Proteome Identify Potential Biomarkers of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is extremely aggressive, has an unfavorable prognosis, and there are no biomarkers for early detection of the disease or identification of individuals at high risk for morbidity or mortality. The cellular and molecular complexity of PDAC leads to inconsistences in clinical validations of many proteins that have been evaluated as prognostic biomarkers of the disease. The tumor secretome, a potential source of biomarkers in PDAC, plays a crucial role in cell proliferation and metastasis, as well as in resistance to treatments, which together contribute to a worse clinical outcome. The massive amount of proteomic data from pancreatic cancer that has been generated from previous studies can be integrated and explored to uncover secreted proteins relevant to the diagnosis and prognosis of the disease. The present study aimed to perform an integrated meta-analysis of PDAC proteome and secretome public data to identify potential biomarkers of the disease. Our meta-analysis combined mass spectrometry data obtained from two systematic reviews of the pancreatic cancer literature, which independently selected 20 studies of the secretome and 35 of the proteome. Next, we predicted the secreted proteins using seven in silico tools or databases, which identified 39 secreted proteins shared between the secretome and proteome data. Notably, the expression of 31 genes of these secretome-related proteins was upregulated in PDAC samples from The Cancer Genome Atlas (TCGA) when compared to control samples from TCGA and The Genotype-Tissue Expression (GTEx). The prognostic value of these 39 secreted proteins in predicting survival outcome was confirmed using gene expression data from four PDAC datasets (validation set). The gene expression of these secreted proteins was able to distinguish high- and low-survival patients in nine additional tumor types from TCGA, demonstrating that deregulation of these secreted proteins may also contribute to the prognosis in multiple cancers types. Finally, we compared the prognostic value of the identified secreted proteins in PDAC biomarkers studies from the literature. This analysis revealed that our gene signature performed equally well or better than the signatures from these previous studies. In conclusion, our integrated meta-analysis of PDAC proteome and secretome identified 39 secreted proteins as potential biomarkers, and the tumor gene expression profile of these proteins in patients with PDAC is associated with worse overall survival.

Cancer metabolomic markers in urine: evidence, techniques and recommendations

Urinary tests have been used as noninvasive, cost-effective tools for screening, diagnosis and monitoring of diseases since ancient times. As we progress through the 21st century, modern analytical platforms have enabled effective measurement of metabolites, with promising results for both a deeper understanding of cancer pathophysiology and, ultimately, clinical translation. The first study to measure metabolomic urinary cancer biomarkers using NMR and mass spectrometry (MS) was published in 2006 and, since then, these techniques have been used to detect cancers of the urological system (kidney, prostate and bladder) and nonurological tumours including those of the breast, ovary, lung, liver, gastrointestinal tract, pancreas, bone and blood. This growing field warrants an assessment of the current status of research developments and recommendations to help systematize future research.

Omics Approaches in Pancreatic Adenocarcinoma

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.

Ocoxin Oral Solution Exerts an Antitumoral Effect in Pancreatic Cancer and Reduces the Stromal-Mediated Chemoresistance

OBJECTIVES

Pancreatic carcinoma is one of the most aggressive cancers overcoming chemoresistance. Thus, novel compounds to complement the current antitumor agents are in need. Ocoxin oral solution (OOS) has proven antioxidant, anti-inflammatory, and antistromagenic properties. The aim of this study was to analyze the effect of OOS in an experimental pancreatic cancer model and its implication in stroma-related chemoresistance to paclitaxel and gemcitabine.

METHODS

Murine pancreatic carcinoma 266-6 cells were treated with OOS to analyze cell cycle and to perform a mRNA comparative microarray study. Then the viability was assessed in combination with paclitaxel and/or gemcitabine. Chemoresistance induced by the medium taken from fibroblast cultures was also investigated on 6 human pancreatic carcinoma cell lines. Furthermore, an experimental model of pancreatic cancer was carried out to study the effect of OOS in vivo.

RESULTS

Ocoxin oral solution enhances the cytotoxic effect of paclitaxel and gemcitabine, while it ameliorates the chemoresistance induced by fibroblast-derived soluble factors in human pancreatic cancer cells. The OOS also promotes the regulation of the expression of genes that are altered in pancreatic carcinoma and slows down 266-6 cell pancreatic tumor development in vivo.

CONCLUSIONS

Ocoxin oral solution could be a potential complement to the chemotherapeutic drugs for pancreatic adenocarcinoma.

Application of Isobaric Tags for Relative and Absolute Quantification (iTRAQ) Coupled with Two-Dimensional Liquid Chromatography/Tandem Mass Spectrometry in Quantitative Proteomic Analysis for Discovery of Serum Biomarkers for Idiopathic Pulmonary Fibrosis

Background

The present study was performed to explore the presence of informative protein biomarkers of human serum proteome in idiopathic pulmonary fibrosis (IPF).

Material/Methods

Serum samples were profiled using iTRAQ coupled with two-dimensional liquid chromatography/tandem mass spectrometry (2D-LC-MS/MS) technique, and ELISA was used to validate candidate biomarkers.

Results

A total of 394 proteins were identified and 97 proteins were associated with IPF. Four biomarker candidates generated from iTRAQ experiments – CRP, fibrinogen-α chain, haptoglobin, and kininogen-1 – were successfully verified using ELISA.

Conclusions

The present study demonstrates that levels of CRP and fibrinogen-α are higher and levels of haptoglobin and kininogen-1 are lower in patients with IPF compared to levels in healthy controls. We found they are useful candidate biomarkers for IPF.

CD59: a promising target for tumor immunotherapy

CD59 has been identified as a glycosylphosphatidylinositol-anchored membrane protein that acts as an inhibitor of the formation of the membrane attack complex to regulate complement activation. Recent studies have shown that CD59 is highly expressed in several cancer cell lines and tumor tissues. CD59 also regulates the function, infiltration and phenotypes of a variety of immune cells in the tumor microenvironment. Herein, we summarized recent advances related to the functions and mechanisms of CD59 in the tumor microenvironment. Therapeutic strategies that seek to modulate the functions of CD59 in the tumor microenvironment could be a promising direction for tumor immunotherapy.

Advances in Pancreatic Biomarker Measures: A Novel Approach to An Obscure Organ

The pancreas remains a challenging organ to assess because of its retroperitoneal locations and cost of accessing the pancreatic duct for collection of biological samples. A novel and potentially useful approach to analysis of pancreatic juice proteins has been developed by Rocker et al. (Clin Transl Gastroenterol 7: e174; doi:10.1038/ctg.2016.27) using whole-gut lavage fluid from a colonoscopy prep. The widespread use of colonoscopy for colon cancer screening provides the opportunity to also screen the patient for benign and malignant pancreatic diseases using the fluid waste. New approaches are needed to assessing the pancreas, and wastes should not be wasted.

Urinary Peptide Analysis Differentiates Pancreatic Cancer From Chronic Pancreatitis

OBJECTIVES

Differentiation of pancreatic cancer (PCA) from chronic pancreatitis (CP) is challenging. We searched for peptide markers in urine to develop a diagnostic peptide marker model.

METHODS

Capillary electrophoresis-mass spectrometry was used to search for peptides in urine of patients with PCA (n = 39) or CP (n = 41). Statistical different peptides were included in a peptide multimarker model. Peptide markers were sequence identified and validated by immunoassay and immunohistochemistry (IHC).

RESULTS

Applied to a validation cohort of 54 patients with PCA and 52 patients with CP, the peptide model correctly classified 47 patients with PCA and 44 patients with CP (area under the curve, 0.93; 87% sensitivity; 85% specificity). All 5 patients with PCA with concomitant CP were classified positive. Urine proteome analysis outperformed carbohydrate antigen 19-9 (area under the curve, 0.84) by a 15% increase in sensitivity at the same specificity. From 99 healthy subjects, only four were misclassified. Fetuin-A was the most prominent peptide marker source for PCA as verified by immunoassay and IHC. In silico protease mapping of the peptide markers' terminal sequences pointed to increased meprin-A activity in PCA, which in IHC was associated with neoangiogenesis.

CONCLUSIONS

Urinary proteome analysis differentiates PCA from CP and may serve as PCA screening tool.

A Group of Novel Serum Diagnostic Biomarkers for Multidrug-Resistant Tuberculosis by iTRAQ-2D LC-MS/MS and Solexa Sequencing

The epidemic of pulmonary tuberculosis (TB), especially multidrug-resistance tuberculosis (MDR-TB) presented a major challenge for TB treatment today. We performed iTRAQ labeling coupled with two-dimensional liquid chromatography-tandem mass spectrometry (2D LC-MS/MS) and Solexa sequencing among MDR-TB patients, drug-sensitive tuberculosis (DS-TB) patients, and healthy controls. A total of 50 differentially expressed proteins and 43 differentially expressed miRNAs (fold change >1.50 or <0.60, P<0.05) were identified in the MDR-TB patients compared to both DS-TB patients and healthy controls. We found that 22.00% of differentially expressed proteins and 32.56% of differentially expressed miRNAs were related, and could construct a network mainly in complement and coagulation cascades. Significant differences in CD44 antigen (CD44), coagulation factor XI (F11), kininogen-1 (KNG1), miR-4433b-5p, miR-424-5p, and miR-199b-5p were found among MDR-TB patients, DS-TB patients and healthy controls (P<0.05) by enzyme-linked immunosorbent assay (ELISA) and SYBR green qRT-PCR validation. A strong negative correlation, consistent with the target gene prediction, was found between miR-199b-5p and KNG1 (r=-0.232, P=0.017). Moreover, we established the MDR-TB diagnostic model based on five biomarkers (CD44, KNG1, miR-4433b-5p, miR-424-5p, and miR-199b-5p). Our study proposes potential biomarkers for MDR-TB diagnosis, and also provides a new experimental basis to understand the pathogenesis of MDR-TB.

Identification of a Three-Biomarker Panel in Urine for Early Detection of Pancreatic Adenocarcinoma

PURPOSE

Noninvasive biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are currently not available. Here, we aimed to identify a set of urine proteins able to distinguish patients with early-stage PDAC from healthy individuals.

EXPERIMENTAL DESIGN

Proteomes of 18 urine samples from healthy controls, chronic pancreatitis, and patients with PDAC (six/group) were assayed using GeLC/MS/MS analysis. The selected biomarkers were subsequently validated with ELISA assays using multiple logistic regression applied to a training dataset in a multicenter cohort comprising 488 urine samples.

RESULTS

LYVE-1, REG1A, and TFF1 were selected as candidate biomarkers. When comparing PDAC (n = 192) with healthy (n = 87) urine specimens, the resulting areas under the receiver-operating characteristic curves (AUC) of the panel were 0.89 [95% confidence interval (CI), 0.84-0.94] in the training (70% of the data) and 0.92 (95% CI, 0.86-0.98) in the validation (30% of the data) datasets. When comparing PDAC stage I-II (n = 71) with healthy urine specimens, the panel achieved AUCs of 0.90 (95% CI, 0.84-0.96) and 0.93 (95% CI, 0.84-1.00) in the training and validation datasets, respectively. In PDAC stage I-II and healthy samples with matching plasma CA19.9, the panel achieved a higher AUC of 0.97 (95% CI, 0.94-0.99) than CA19.9 (AUC = 0.88; 95% CI, 0.81-0.95, P = 0.005). Adding plasma CA19.9 to the panel increased the AUC from 0.97 (95% CI, 0.94-0.99) to 0.99 (95% CI, 0.97-1.00, P = 0.04), but did not improve the comparison of stage I-IIA PDAC (n = 17) with healthy urine.

CONCLUSIONS

We have established a novel, three-protein biomarker panel that is able to detect patients with early-stage pancreatic cancer in urine specimens.

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.

Biomarkers screening between preoperative and postoperative patients in pancreatic cancer

OBJECTIVE

To investigate discriminating protein patterns and potential biomarkers in serum samples between pre/postoperative pancreatic cancer patients and healthy controls.

METHODS

23 serum samples from PC patients (12 preoperative and 11 postoperative) and 76 from healthy controls were analyzed using matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS) technique combined with magnetic beads-based weak cation-exchange chromatography (MB-WCX). ClinProTools software selected several markers that made a distinction between pancreatic cancer patients and healthy controls.

RESULTS

49 m/z distinctive peaks were found among the three groups, of which 33 significant peaks with a P < 0.001 were detected. Two proteins could distinguish the preoperative pancreatic cancer patients from the healthy controls. About 15 proteins may be potential biomarkers in assessment of pancreatic cancer resection.

CONCLUSION

MB-MALDI-TOF-MS method could generate serum peptidome profiles of pancreatic cancer and provide a new approach to identify potential biomarkers for diagnosis and prognosis of this malignancy.

Alkaline phosphatase ALPPL-2 is a novel pancreatic carcinoma-associated protein

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a very low median survival rate. The lack of early sensitive diagnostic markers is one of the main causes of PDAC-associated lethality. Therefore, to identify novel pancreatic cancer biomarkers that can facilitate early diagnosis and also help in the development of effective therapeutics, we developed RNA aptamers targeting pancreatic cancer by Cell-systematic evolution of ligands by exponential enrichment (SELEX) approach. Using a selection strategy that could generate aptamers for 2 pancreatic cancer cell lines in one selection scheme, we identified an aptamer SQ-2 that could recognize pancreatic cancer cells with high specificity. Next, by applying 2 alternative approaches: (i) aptamer-based target pull-down and (ii) genome-wide microarray-based identification of differentially expressed mRNAs in aptamer-positive and -negative cells, we identified alkaline phosphatase placental-like 2 (ALPPL-2), an oncofetal protein, as the target of SQ-2. ALPPL-2 was found to be ectopically expressed in many pancreatic cancer cell lines at both mRNA and protein levels. RNA interference-mediated ALPPL-2 knockdown identified novel tumor-associated functions of this protein in pancreatic cancer cell growth and invasion. In addition, the aptamer-mediated identification of ALPPL-2 on the cell surface and cell secretions of pancreatic cancer cells supports its potential use in the serum- and membrane-based diagnosis of PDAC.

Detection of differential levels of proteins in the urine of patients with endometrial cancer: analysis using two-dimensional gel electrophoresis and o-glycan binding lectin

Cancers can cause some proteins to be aberrantly excreted or released in the urine, which can be used as biomarkers. To screen for potential biomarkers for endometrial cancer (ECa), the urinary proteins from patients who were newly diagnosed with early stage ECa and untreated controls were separated using two-dimensional gel electrophoresis (2-DE) and followed by image analysis. The altered levels of zinc alpha-2 glycoprotein, alpha 1-acid glycoprotein, and CD59 were detected in the patients compared to the controls. In addition, the urine of the ECa patients was also found to contain relatively lower levels of a fragment of nebulin when the 2-DE separated urinary proteins were probed using champedak galactose binding (CGB) lectin. The different levels of the nebulin fragment were further validated by subjecting the urinary protein samples to CGB lectin affinity chromatography and analysis of the bound fractions by LC-MS/MS. Our data is suggestive of the potential use of the differentially expressed urinary proteins as biomarkers for ECa although this requires further extensive validation on clinically representative populations.

Diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis by measurement of microRNA abundance in blood and tissue

A solid process for diagnosis could have a substantial impact on the successful treatment of pancreatic cancer, for which currently mortality is nearly identical to incidence. Variations in the abundance of all microRNA molecules from peripheral blood cells and pancreas tissues were analyzed on microarrays and in part validated by real-time PCR assays. In total, 245 samples from two clinical centers were studied that were obtained from patients with pancreatic ductal adenocarcinoma or chronic pancreatitis and from healthy donors. Utilizing the minimally invasive blood test, receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC) analysis demonstrated very high sensitivity and specificity of a distinction between healthy people and patients with either cancer or chronic pancreatitis; respective AUC values of 0.973 and 0.950 were obtained. Confirmative and partly even more discriminative diagnosis could be performed on tissue samples with AUC values of 1.0 and 0.937, respectively. In addition, discrimination between cancer and chronic pancreatitis was achieved (AUC = 0.875). Also, several miRNAs were identified that exhibited abundance variations in both tissue and blood samples. The results could have an immediate diagnostic value for the evaluation of tumor reoccurrence in patients, who have undergone curative surgical resection, and for people with a familial risk of pancreatic cancer.

Proteome of formalin-fixed paraffin-embedded pancreatic ductal adenocarcinoma and lymph node metastases

Pancreatic ductal adenocarcinoma (PDAC) is a major cause of cancer-related death, largely due to metastatic disease. To better understand PDAC metastatic spread and identify novel therapeutic targets, we analysed the proteome of primary tumours and matched lymph node (LN) metastases. As frozen specimens of metastatic lesions are scarce, we examined formalin-fixed paraffin-embedded (FFPE) tissues. This poses technical challenges because of the cross-linkages induced by fixation. Using laser capture microdissection (PALM system), we isolated malignant epithelia from seven FFPE primary PDAC tumours and matched LN metastases. Following dissection, samples were analysed in duplicate using Multidimensional Protein Identification Technology (MudPIT); this resulted in the identification of 1504 proteins, 854 of which were common to all samples analysed. Comparison of the obtained proteins with data from previous proteomics studies on pancreatic tissue, pancreatic juice, serum, and urine resulted in a less than 30% overlap, indicating that our study has substantially expanded the current database of proteins expressed in this malignancy. Statistical analysis further showed that 115/854 proteins (13.5%) were significantly differentially expressed (g-value ≥ 3.8). Two proteins, S100P and 14-3-3 sigma, with highly significant g-values were confirmed to be significantly differentially expressed (S100P: p = 0.05 and 14-3-3 sigma: p < 0.001) in a larger series of 55 cases of matched primary PDAC and LN metastases using immunohistochemistry. Thus, laser capture microdissection of FFPE tissue coupled with downstream proteomic analysis is a valid approach for the investigation of metastatic PDAC. This is the first study to establish and compare the protein composition of primary PDAC and matched LN metastases, and has resulted in the identification of several potential epithelial-specific therapeutic targets, including 14-3-3 sigma and S100P.

Proteome-based biomarkers in pancreatic cancer

Pancreatic cancer, as a highly malignant cancer and the fourth cause of cancer-related death in world, is characterized by dismal prognosis, due to rapid disease progression, highly invasive tumour phenotype, and resistance to chemotherapy. Despite significant advances in treatment of the disease during the past decade, the survival rate is little improved. A contributory factor to the poor outcome is the lack of appropriate sensitive and specific biomarkers for early diagnosis. Furthermore, biomarkers for targeting, directing and assessing therapeutic intervention, as well as for detection of residual or recurrent cancer are also needed. Thus, the identification of adequate biomarkers in pancreatic cancer is of extreme importance. Recently, accompanying the development of proteomic technology and devices, more and more potential biomarkers have appeared and are being reported. In this review, we provide an overview of the role of proteome-based biomarkers in pancreatic cancer, including tissue, serum, juice, urine and cell lines. We also discuss the possible mechanism and prospects in the future. That information hopefully might be helpful for further research in the field.

-The advancement of biomarker-based diagnostic tools for ovarian, breast, and pancreatic cancer through the use of urine as an analytical biofluid

Despite considerable advancements, the development of effective cancer screening tools based on serum biomarker measurements has thus far failed to achieve a meaningful clinical impact. The incremental progress observed over the course of serum biomarker development suggests that further refinements based on novel approaches may yet result in a breakthrough. The use of urine as an analytical biofluid for biomarker development may represent such an approach. The unique characteristics of urine including a high level of stability, ease of sampling, and an inactive and low-complexity testing matrix offer several potential advantages over the use of serum. A number of recent reports have demonstrated the utility of urine in the identification of novel cancer biomarkers and also the improved performance of biomarkers previously evaluated in serum. In this review, advancements related to the use of urine biomarkers within the settings of ovarian, breast, and pancreatic cancer are presented and discussed. Findings regarding the identification of specific urine biomarkers for each disease are highlighted along with comparative analyses of urine and serum biomarkers as diagnostic tools.

A functional proteomic method for biomarker discovery

The sequencing of the human genome holds out the hope for personalized medicine, but it is clear that analysis of DNA or RNA content alone is not sufficient to understand most disease processes. Proteomic strategies that allow unbiased identification of proteins and their post-transcriptional and -translation modifications are an essential complement to genomic strategies. However, the enormity of the proteome and limitations in proteomic methods make it difficult to determine the targets that are particularly relevant to human disease. Methods are therefore needed that allow rational identification of targets based on function and relevance to disease. Screening methodologies such as phage display, SELEX, and small-molecule combinatorial chemistry have been widely used to discover specific ligands for cells or tissues of interest, such as tumors. Those ligands can be used in turn as affinity probes to identify their cognate molecular targets when they are not known in advance. Here we report an easy, robust and generally applicable approach in which phage particles bearing cell- or tissue-specific peptides serve directly as the affinity probes for their molecular targets. For proof of principle, the method successfully identified molecular binding partners, three of them novel, for 15 peptides specific for pancreatic cancer.

Proteomics and systems biology: current and future applications in the nutritional sciences

In the last decade, advances in genomics, proteomics, and metabolomics have yielded large-scale datasets that have driven an interest in global analyses, with the objective of understanding biological systems as a whole. Systems biology integrates computational modeling and experimental biology to predict and characterize the dynamic properties of biological systems, which are viewed as complex signaling networks. Whereas the systems analysis of disease-perturbed networks holds promise for identification of drug targets for therapy, equally the identified critical network nodes may be targeted through nutritional intervention in either a preventative or therapeutic fashion. As such, in the context of the nutritional sciences, it is envisioned that systems analysis of normal and nutrient-perturbed signaling networks in combination with knowledge of underlying genetic polymorphisms will lead to a future in which the health of individuals will be improved through predictive and preventative nutrition. Although high-throughput transcriptomic microarray data were initially most readily available and amenable to systems analysis, recent technological and methodological advances in MS have contributed to a linear increase in proteomic investigations. It is now commonplace for combined proteomic technologies to generate complex, multi-faceted datasets, and these will be the keystone of future systems biology research. This review will define systems biology, outline current proteomic methodologies, highlight successful applications of proteomics in nutrition research, and discuss the challenges for future applications of systems biology approaches in the nutritional sciences.

Patients with ovarian carcinoma excrete different altered levels of urine CD59, kininogen-1 and fragments of inter-alpha-trypsin inhibitor heavy chain H4 and albumin

Background

Diagnosis of ovarian carcinoma is in urgent need for new complementary biomarkers for early stage detection. Proteins that are aberrantly excreted in the urine of cancer patients are excellent biomarker candidates for development of new noninvasive protocol for early diagnosis and screening purposes. In the present study, urine samples from patients with ovarian carcinoma were analysed by two-dimensional gel electrophoresis and the profiles generated were compared to those similarly obtained from age-matched cancer negative women.

Results

Significant reduced levels of CD59, kininogen-1 and a 39 kDa fragment of inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), and enhanced excretion of a 19 kDa fragment of albumin, were detected in the urine of patients with ovarian carcinoma compared to the control subjects. The different altered levels of the proteins were confirmed by Western blotting using antisera and a lectin that bind to the respective proteins.

Conclusion

CD59, kininogen-1 and fragments of ITIH4 and albumin may be used as complementary biomarkers in the development of new noninvasive protocols for diagnosis and screening of ovarian carcinoma.

Current status of molecular markers for early detection of sporadic pancreatic cancer

Pancreatic cancer (PC) is a highly lethal malignancy with near 100% mortality. This is in part due to the fact that most patients present with metastatic or locally advanced disease at the time of diagnosis. Significantly, in nearly 95% of PC patients there is neither an associated family history of PC nor of diseases known to be associated with an increased risk of PC. These groups of patients who comprise the bulk of PC cases are termed as "sporadic PC" in contrast to the familial PC cases that comprise only about 5% of all PCs. Given the insidious onset of the malignancy and its extreme resistance to chemo and radiotherapy, an abundance of research in recent years has focused on identifying biomarkers for the early detection of PC, specifically aiming at the sporadic PC cohort. However, while several studies have established that asymptomatic individuals with a positive family history of PC and those with certain heritable syndromes are candidates for PC screening, the role of screening in identifying sporadic PC is still an unsettled question. The present review attempts to assess this critical question by investigating the recent advances made in molecular markers with potential use in the early diagnosis of sporadic PC - the largest cohort of PC cases worldwide. It also outlines a novel yet simple risk factor based stratification system that could be potentially employed by clinicians to identify those individuals who are at an elevated risk for the development of sporadic PC and therefore candidates for screening.

Dual-color proteomic profiling of complex samples with a microarray of 810 cancer-related antibodies

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses.

Urinary proteome profiling using 2D-DIGE and LC-MS/MS

Proteomic methodologies have been at the forefront of cancer research for several years. The use of proteomic strategies to study all expressed genes aims to discover biomarkers indicative of the physiological state of cancer cells at specific time points, enabling early diagnosis, following cancer development/progression, screening and monitoring the efficacy of new therapeutic agents. Onco-proteomics has the potential to impact on oncology practice by delivering individualised highly selective clinical care. 2D-DIGE (2D difference in gel electrophoresis) enables simultaneous examination and comparison of multiple samples using cyanine dyes to label amino acid residues that are then separated based on charge and mass. These advantages combined with universal availability have until recently made 2D-DIGE a first method of choice in cancer proteome analysis of diverse specimens, including tissues, cell lines, blood and other body fluids.