Classification of pancreatic cystic lesions using SELDI-TOF mass spectrometry

Pancreatic Cystic Lesions: A Focused Review on Cyst Clinicopathological Features and Advanced Diagnostics

Macroscopic, endomicroscopic, and histologic findings and correlation are an integral part of the diagnostic evaluation of pancreatic cystic lesions (PCLs), as complementing morphologic features seen by different specialties are combined to contribute to a final diagnosis. However, malignancy risk stratification of PCLs with worrisome features can still be challenging even after endoscopic ultrasound guided-fine needle aspiration (EUS-FNA) with cytological evaluation. This review aims to summarize cyst clinicopathological features from the pathologists' perspective, coupled with knowledge from advanced diagnostics-confocal laser endomicroscopy and cyst fluid molecular analysis, to demonstrate the state-of-art risk stratification of PCLs. This review includes illustrative photos of surgical specimens, endomicroscopic and histologic images, and a summary of cyst fluid molecular markers.

Discovery and Validation of Biomarkers That Distinguish Mucinous and Nonmucinous Pancreatic Cysts

The use of advanced imaging technologies for the identification of pancreatic cysts has become widespread. However, accurate differential diagnosis between mucinous cysts (MC) and nonmucinous cysts (NMC) consisting of pseudocysts (NMC1) and nonmucinous neoplastic cysts (NMC2) remains a challenge. Thus, it is necessary to develop novel biomarkers for the differential diagnosis of pancreatic cysts. An integrated proteomics approach yielded differentially expressed proteins in MC that were verified subsequently in 99 pancreatic cysts (21 NMC1, 41 NMC2, and 37 MC) using a method termed GeLC-stable isotope dilution-multiple reaction monitoring-mass spectrometry (GeLC-SID-MRM-MS) along with established immunoassay techniques. We identified 223 proteins by nanoscale liquid chromatography coupled to tandem mass spectrometry (nano LC/MS-MS). Nine candidate biomarkers were identified, including polymeric immunoglobulin receptor (PIGR), lipocalin 2 (LCN2), Fc fragment of IgG-binding protein (FCGBP), lithostathine-1-alpha (REG1A), afamin (AFM), chymotrypsin C (caldecrin; CTRC), amylase, alpha 2B (pancreatic; AMY2B), lectin, galactoside-binding, soluble, 3 binding protein (LGALS3BP), and chymotrypsin-like elastase family, member 3A (CELA3A), which were established as biomarker candidates for MC. In particular, we have shown that a biomarker subset, including AFM, REG1A, PIGR, and LCN2, could differentiate MC not only from NMC (including NMC1) but also from NMC2. Overall, the MS-based comprehensive proteomics approach used in this study established a novel set of candidate biomarkers that address a gap in efforts to distinguish early pancreatic lesions at a time when more successful therapeutic interventions may be possible.

Systematic Review of Pancreatic Cyst Fluid Biomarkers: The Path Forward

There is significant research interest in developing and validating novel pancreatic cyst-fluid biomarkers given the increasing recognition of the prevalence of pancreatic cysts and their associated malignant potential. Although current international consensus guidelines are helpful, they fail to diagnose with certainty the cyst type and the level of epithelial dysplasia. They also fall short in predicting the future likelihood of malignant transformation. A systematic review was performed with the objective of summarizing cyst-fluid-based biomarkers that have been published in the medical literature over the past 10 years and characterizing the current quality of evidence. Our review demonstrates that there is an increasing interest in this topic with several different and innovative approaches including DNA, RNA, proteomic, and metabolomics profiling. Further techniques to improve upon cytological yield have also been studied. Besides identifying potentially useful clinical biomarkers, these empiric approaches have provided further insight into their pathogenesis. The level of evidence for the vast majority of these studies, however, is limited to retrospective early validation studies. The path forward will be to select out the most promising biomarkers and develop multicenter consortiums capable of capturing adequate sample sizes with appropriate study designs.

Proteomic mucin profiling for the identification of cystic precursors of pancreatic cancer

BACKGROUND

Pancreatic cystic lesions (PCLs) are increasingly frequent radiological incidentalomas, with a considerable proportion representing precursors of pancreatic cancer. Better diagnostic tools are required for patients to benefit from this development.

METHODS

To evaluate whether cyst fluid mucin expression could predict malignant potential and/or transformation in PCLs, a proteomic method was devised and prospectively evaluated in consecutive patients referred to our tertiary center for endoscopic ultrasound-guided aspiration of cystic lesions from May 2007 through November 2008 (discovery cohort) and from December 2008 through October 2012 (validation cohort). Cytology and cyst fluid carcinoembryonic antigen (CEA; premalignancy > 192 ng/mL, malignancy > 1000 ng/mL) were routinely analyzed, and samples were further processed as follows: one-dimensional gel electrophoresis, excision of high-mass areas, tryptic digestion and nano-liquid chromatography-tandem mass spectrometry, with peptide identification by Mascot software and an in-house mucin database. All diagnostic evaluations were blinded to proteomics results. Histology was required to confirm the presence/absence of malignant transformation. All statistical tests were two-sided.

RESULTS

Proteomic mucin profiling proved statistically significantly more accurate (97.5%; 95% confidence interval [CI] = 90.3% to 99.6%) than cytology (71.4%; 95% CI = 59.8% to 80.9%; P < .001) and cyst fluid CEA (78.0%; 95% CI = 65.0% to 87.3%; P < .001) in identifying the 37 (out of 79; 46.8%) lesions with malignant potential (ie, premalignant or malignant tumors). The accuracy of proteomics was nearly identical (96.6% vs 98.0%) between the discovery (n = 29) and validation (n = 50) cohorts. Furthermore, mucin profiling predicted malignant transformation, present in 16 out of 29 (discovery cohort: 9, validation cohort: 20) lesions with available histology, with 89.7% accuracy (95% CI = 71.5% to 97.3%) (for the validation cohort only: 95.0%; 95% CI = 73.1% to 99.7%). This markedly exceeded corresponding results for cytology (51.7%; 95% CI = 32.9% to 70.1%; P = .003) and CEA (57.1%; 95% CI = 34.4% to 77.4%; P = .02).

CONCLUSIONS

Proteomic cyst fluid mucin profiling robustly discriminates benign, premalignant, and malignant PCLs. Consequently, it may improve pancreatic cancer prevention and reduce the morbidity burden of unwarranted pancreatic surgery.

Effect of NaCl and sucrose tastants on protein composition of oral fluid analysed by SELDI-TOF-MS

During eating, human saliva is secreted into the oral cavity by salivary glands. The relative contribution of different glands to total salivary flow rate depends, among other factors, on the tastants in the food. Few reports indicated that also the salivary protein composition depends on the tastant make-up of the food. We studied the influence of sodium-chloride- and sucrose solutions on the presence of proteins in the M(r) range 2-20kDa in whole saliva. Upon oral stimulation with a sodium chloride solution, a sucrose solution or water, we collected whole saliva from 14 volunteers after t=1 min, t=11 min and t=20 min. Saliva protein profiles were analysed by SELDI-TOF-MS. SELDI-TOF-MS intensities of m/z values representing different protein masses were compared between subjects, tastants and time conditions. For subsets of the 33 detected masses, significant effects were observed for all factors, with most masses involved in the Subjects effect: m/z(Subjects)>m/z(Time×Stimulus)>m/z(Stimulus)>m/z(Time). Most effects on saliva protein composition were observed at t=1 min, whilst almost no effects were observed at t=11 min and t=20 min. When considering the Stimulus×Time interaction, we identified four different stimulus-response patterns. Proteins identified in the present study, and attributed to specific glands or tissues in literature, were used to associate stimulus-response patterns with tissue provenances. Observed stimulus-response patterns were not uniquely associated to particular glands and tissues. Hence, there was no evidence of the involvement of particular tissues or glands in tastant-specific protein responses. In conclusion, oral stimulation with different tastants affects salivary protein composition in a protein- and stimuli dependent way, which seems not be associated with any specific tissues or glands of origin.

Glycomic and proteomic profiling of pancreatic cyst fluids identifies hyperfucosylated lactosamines on the N-linked glycans of overexpressed glycoproteins

Pancreatic cancer is now the fourth leading cause of cancer deaths in the United States, and it is associated with an alarmingly low 5-year survival rate of 5%. However, a patient's prognosis is considerably improved when the malignant lesions are identified at an early stage of the disease and removed by surgical resection. Unfortunately, the absence of a practical screening strategy and clinical diagnostic test for identifying premalignant lesions within the pancreas often prevents early detection of pancreatic cancer. To aid in the development of a molecular screening system for early detection of the disease, we have performed glycomic and glycoproteomic profiling experiments on 21 pancreatic cyst fluid samples, including fluids from mucinous cystic neoplasms and intraductal papillary mucinous neoplasms, two types of mucinous cysts that are considered high risk to undergo malignant transformation. A total of 80 asparagine-linked (N-linked) glycans, including high mannose and complex structures, were identified. Of special interest was a series of complex N-linked glycans containing two to six fucose residues, located predominantly as substituents on β-lactosamine extensions. Following the observation of these "hyperfucosylated" glycans, bottom-up proteomics experiments utilizing a label-free quantitative approach were applied to the investigation of two sets of tryptically digested proteins derived from the cyst fluids: 1) all soluble proteins in the raw samples and 2) a subproteome of the soluble cyst fluid proteins that were selectively enriched for fucosylation through the use of surface-immobilized Aleuria aurantia lectin. A comparative analysis of these two proteomic data sets identified glycoproteins that were significantly enriched by lectin affinity. Several candidate glycoproteins that appear hyperfucosylated were identified, including triacylglycerol lipase and pancreatic α-amylase, which were 20- and 22-fold more abundant, respectively, following A. aurantia lectin enrichment.

Mass spectrometry-based proteomics of endoscopically collected pancreatic fluid in chronic pancreatitis research

MS-based investigation of pancreatic fluid enables the high-throughput identification of proteins present in the pancreatic secretome. Pancreatic fluid is a complex admixture of digestive, inflammatory, and other proteins secreted by the pancreas into the duodenum, and thus is amenable to MS-based proteomic analysis. Recent advances in endoscopic techniques, in particular the endoscopic pancreatic function test (ePFT), have improved the collection methodology of pancreatic fluid for proteomic analysis. Here, we provide an overview of MS-based proteomic techniques as applied to the study of pancreatic fluid. We address sample collection, protein extraction, MS sample preparation and analysis, and bioinformatic approaches, and summarize current MS-based investigations of pancreatic fluid. We then examine the limitations and the future potential of such technologies in the investigation of pancreatic disease. We conclude that pancreatic fluid represents a rich reservoir of potential biomarkers and that the study of the molecular mechanisms of chronic pancreatitis may benefit substantially from MS-based proteomics.

The use of protein-based biomarkers for the diagnosis of cystic tumors of the pancreas

Proteomics is a powerful method used to identify, characterize, and quantify proteins within biologic samples. Pancreatic cystic neoplasms are a common clinical entity and represent a diagnostic and management challenge due to difficulties in accurately diagnosing cystic lesions with malignant potential and assessing the risk of malignant degeneration. Currently, cytology and other biomarkers in cyst fluid have had limited success in accurately distinguishing both the type of cystic neoplasm and the presence of malignancy. Emerging data suggests that the use of protein-based biomarkers may have greater utility in helping clinicians correctly diagnose the type of cyst and to identify which cystic neoplasms are malignant. Several candidate proteins have been identified within pancreatic cystic neoplasms as potential biomarkers. Future studies will be needed to validate these findings and move these biomarkers into the clinical setting.

Pancreatic cancer biomarkers discovery by surface-enhanced laser desorption and ionization time-of-flight mass spectrometry

BACKGROUND

Surface-enhanced laser desorption and ionization time-of-flight mass spectrometry (SELDI-TOF/MS), a laboratory-friendly technique, is used to identify biomarkers for cancer. The aim of the present study was to explore the application of SELDI proteomic patterns in serum for distinguishing between cases of pancreatic cancer, chronic pancreatitis, type 2 diabetes mellitus and healthy controls.

METHODS

Sera from 12 healthy controls, 24 patients with type 2 diabetes mellitus, 126 with pancreatic cancer, including 84 with diabetes, and 61 with chronic pancreatitis, 32 of which were diabetics, were analyzed using SELDI-TOF/MS. Spectra (IMAC-30) were clustered and classified using Biomarker Wizard and Biomarker Pattern software.

RESULTS

Two decision tree classification algorithms, one with and one without CA 19-9, were constructed. In the absence of CA 19-9, the splitting protein peaks were: m/z 1526, 1211, and 3519; when CA 19-9 was used in the analysis, it replaced the m/z 3519 splitter. The two algorithms performed equally for classifying patients. A classification tree that considered diabetic patients only was constructed; the main splitters were: 1211, CA 19-9, 7903, 3359, 1802. With this algorithm, 100% of patients with type 2 diabetes mellitus, 97% with chronic pancreatitis and 77% of patients with pancreatic cancer were correctly classified. SELDI-TOF/MS features improved the diagnostic accuracy of CA 19-9 (AUC = 0.883 for CA 19-9; AUC = 0.935 for CA 19-9 and SELDI-TOF/MS features combined).

CONCLUSIONS

SELDI-TOF/MS allows identification of new peptides which, in addition to CA 19-9, enable the correct classification of the vast majority of patients with pancreatic cancer, which can be distinguished from patients with chronic pancreatitis or type 2 diabetes mellitus.

Cystic neoplasms of the pancreas: A diagnostic challenge

Cystic neoplasms of the pancreas are increasingly recognized due to the expanding use and improved sensitivity of cross-sectional abdominal imaging. Major advances in the last decade have led to an improved understanding of the various types of cystic lesions and their biologic behavior. Despite significant improvements in imaging technology and the advent of endoscopic-ultrasound (EUS)-guided fine-needle aspiration, the diagnosis and management of pancreatic cystic lesions remains a significant clinical challenge. The first diagnostic step is to differentiate between pancreatic pseudocyst and cystic neoplasm. If a pseudocyst has been effectively excluded, the cornerstone issue is then to determine the malignant potential of the pancreatic cystic neoplasm. In the majority of cases, the correct diagnosis and successful management is based not on a single test but on incorporating data from various sources including patient history, radiologic studies, endoscopic evaluation, and cyst fluid analysis. This review will focus on describing the various types of cystic neoplasms of the pancreas, their malignant potential, and will provide the clinician with a comprehensive diagnostic approach.