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

Extracellular vesicle analysis of plasma allows differential diagnosis of atypical pancreatic serous cystadenoma

Increased use of cross-sectional imaging has resulted in frequent detection of incidental cystic pancreatic lesions. Serous cystadenomas (SCAs) are benign cysts that do not require surgical intervention unless symptomatic. Unfortunately, up to half of SCAs do not have typical imaging findings ("atypical SCAs"), overlap with potentially malignant precursor lesions, and thus pose a diagnostic challenge. We tested whether the analysis of circulating extracellular vesicle (EV) biomarkers using a digital EV screening technology (DEST) could enhance the discrimination of cystic pancreatic lesions and avoid unnecessary surgical intervention in these atypical SCAs. Analysis of 25 different protein biomarkers in plasma EV from 68 patients identified a putative biomarker signature of Das-1, Vimentin, Chromogranin A, and CAIX with high discriminatory power (AUC of 0.99). Analysis of plasma EV for multiplexed markers may thus be helpful in clinical decision-making.

Multi-Omic Biomarkers as Potential Tools for the Characterisation of Pancreatic Cystic Lesions and Cancer: Innovative Patient Data Integration

Pancreatic cancer (PC) is regarded as one of the most lethal malignant diseases in the world, with GLOBOCAN 2020 estimates indicating that PC was responsible for almost half a million deaths worldwide in 2020. Pancreatic cystic lesions (PCLs) are fluid-filled structures found within or on the surface of the pancreas, which can either be pre-malignant or have no malignant potential. While some PCLs are found in symptomatic patients, nowadays many PCLs are found incidentally in patients undergoing cross-sectional imaging for other reasons-so called 'incidentalomas'. Current methods of characterising PCLs are imperfect and vary hugely between institutions and countries. As such, there is a profound need for improved diagnostic algorithms. This could facilitate more accurate risk stratification of those PCLs that have malignant potential and reduce unnecessary surveillance. As PC continues to have such a poor prognosis, earlier recognition and risk stratification of PCLs may lead to better treatment protocols. This review will focus on the importance of biomarkers in the context of PCLs and PCand outline how current 'omics'-related work could contribute to the identification of a novel integrated biomarker profile for the risk stratification of patients with PCLs and PC.

Elevating pancreatic cystic lesion stratification: Current and future pancreatic cancer biomarker(s)

Pancreatic ductal adenocarcinoma (PDAC) is an incredibly deadly disease with a 5-year survival rate of 9%. The presence of pancreatic cystic lesions (PCLs) confers an increased likelihood of future pancreatic cancer in patients placing them in a high-risk category. Discerning concurrent malignancy and risk of future PCL progression to cancer must be carefully and accurately determined to improve survival outcomes and avoid unnecessary morbidity of pancreatic resection. Unfortunately, current image-based guidelines are inadequate to distinguish benign from malignant lesions. There continues to be a need for accurate molecular and imaging biomarker(s) capable of identifying malignant PCLs and predicting the malignant potential of PCLs to enable risk stratification and effective intervention management. This review provides an update on the current status of biomarkers from pancreatic cystic fluid, pancreatic juice, and seromic molecular analyses and discusses the potential of radiomics for differentiating PCLs harboring cancer from those that do not.

Metabolomics based predictive classifier for early detection of pancreatic ductal adenocarcinoma

The availability of robust classification algorithms for the identification of high risk individuals with resectable disease is critical to improving early detection strategies and ultimately increasing survival rates in PC. We leveraged high quality biospecimens with extensive clinical annotations from patients that received treatment at the Medstar-Georgetown University hospital. We used a high resolution mass spectrometry based global tissue profiling approach in conjunction with multivariate analysis for developing a classification algorithm that would predict early stage PC with high accuracy. The candidate biomarkers were annotated using tandem mass spectrometry. We delineated a six metabolite panel that could discriminate early stage PDAC from benign pancreatic disease with >95% accuracy of classification (Specificity = 0.85, Sensitivity = 0.9). Subsequently, we used multiple reaction monitoring mass spectrometry for evaluation of this panel in plasma samples obtained from the same patients. The pattern of expression of these metabolites in plasma was found to be discordant as compared to that in tissue. Taken together, our results show the value of using a metabolomics approach for developing highly predictive panels for classification of early stage PDAC. Future investigations will likely lead to the development of validated biomarker panels with potential for clinical translation in conjunction with CA-19-9 and/or other biomarkers.

Metabolomic biomarkers of pancreatic cancer: a meta-analysis study

Pancreatic cancer (PC) is an aggressive disease with high mortality rates, however, there is no blood test for early detection and diagnosis of this disease. Several research groups have reported on metabolomics based clinical investigations to identify biomarkers of PC, however there is a lack of a centralized metabolite biomarker repository that can be used for meta-analysis and biomarker validation. Furthermore, since the incidence of PC is associated with metabolic syndrome and Type 2 diabetes mellitus (T2DM), there is a need to uncouple these common metabolic dysregulations that may otherwise diminish the clinical utility of metabolomic biosignatures. Here, we attempted to externally replicate proposed metabolite biomarkers of PC reported by several other groups in an independent group of PC subjects. Our study design included a T2DM cohort that was used as a non-cancer control and a separate cohort diagnosed with colorectal cancer (CRC), as a cancer disease control to eliminate possible generic biomarkers of cancer. We used targeted mass spectrometry for quantitation of literature-curated metabolite markers and identified a biomarker panel that discriminates between normal controls (NC) and PC patients with high accuracy. Further evaluation of our model with CRC, however, showed a drop in specificity for the PC biomarker panel. Taken together, our study underscores the need for a more robust study design for cancer biomarker studies so as to maximize the translational value and clinical implementation.

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.

Vascular endothelial growth factor, a novel and highly accurate pancreatic fluid biomarker for serous pancreatic cysts

BACKGROUND

Mucinous pancreatic cysts (intraductal papillary mucinous neoplasm and mucinous cystic neoplasm) have the potential to progress to invasive pancreatic adenocarcinoma, presenting an opportunity for early detection, prevention, and cure. Serous cystic neoplasms (SCN) have no malignant potential, but can mimic mucinous pancreatic cysts on imaging. Therefore, identification of biomarkers that can distinguish between cystic lesions is critically important. We hypothesize that vascular endothelial growth factor (VEGF)-A levels in pancreatic fluid correlate with pathologic diagnosis.

STUDY DESIGN

Pancreatic cyst/duct fluid samples were prospectively collected from patients undergoing pancreatic resection and correlated with surgical pathology. VEGF levels were detected by ELISA. VEGF-A and VEGF receptor 2 expression in pancreatic tissue was localized by immunohistochemistry. Genetic alterations of the von Hippel-Lindau gene were determined by targeted next-generation sequencing.

RESULTS

Eighty-seven patients met inclusion criteria for enrollment. Final pathologic diagnoses included pseudocyst (n = 9), SCN (n = 17), mucinous cystic neoplasm (n = 24), low/moderate grade intraductal papillary mucinous neoplasm (n = 16), high-grade/invasive intraductal papillary mucinous neoplasm (n = 10), and pancreatic ductal adenocarcinoma (n = 11). VEGF-A was significantly upregulated in SCN cyst fluid compared with all other diagnoses (p < 0.0001). With a cut-off of 8,500 pg/mL, VEGF-A has 100% sensitivity and 97% specificity as an SCN biomarker. VEGF-A and VEGF receptor 2 are overexpressed in SCN cyst tissue. VEGF-C was also significantly elevated in SCN cyst fluid (p < 0.0001). With a cut-off set at 200 pg/mL, VEGF-C identifies SCN with 100% sensitivity and 90% specificity. The presence of a von Hippel-Lindau mutation in SCN cyst tissue correlates with elevated cyst fluid VEGF levels.

CONCLUSIONS

This is the first report of a cyst fluid protein biomarker that can positively identify SCN. The ability to distinguish SCN from premalignant/malignant pancreatic cysts can spare the cost and risk of surveillance and surgical intervention in select patients.

Characterization of glycoproteins in pancreatic cyst fluid using a high-performance multiple lectin affinity chromatography platform

Currently, pancreatic cancer is the fourth cause of cancer death. In 2013, it is estimated that ∼38 460 people will die of pancreatic cancer. Early detection of malignant cyst (pancreatic cancer precursor) is necessary to help prevent late diagnosis of the tumor. In this study, we characterized glycoproteins and nonglycoproteins on pooled mucinous (n = 10) and nonmucinous (n = 10) pancreatic cyst fluid to identify "proteins of interest" to differentiate between mucinous cyst from nonmucinous cyst and investigate these proteins as potential biomarker targets. An automated multilectin affinity chromatography (M-LAC) platform was utilized for glycoprotein enrichment followed by nano-LC-MS/MS analysis. Spectral count quantitation allowed for the identification of proteins with significant differential levels in mucinous cysts from nonmucinous cysts of which one protein (periostin) was confirmed via immunoblotting. To exhaustively evaluate differentially expressed proteins, we used a number of proteomic tools including gene ontology classification, pathway and network analysis, Novoseek data mining, and chromosome gene mapping. Utilization of complementary proteomic tools revealed that several of the proteins such as mucin 6 (MUC6), bile salt-activated lipase (CEL), and pyruvate kinase lysozyme M1/M2 with significant differential expression have strong association with pancreatic cancer. Furthermore, chromosome gene mapping demonstrated coexpressions and colocalization of some proteins of interest including 14-3-3 protein epsilon (YWHAE), pigment epithelium derived factor (SERPINF1), and oncogene p53.

Clinical decision making in the management of pancreatic cystic neoplasms

Pancreatic cystic lesions continue to pose diagnostic and management dilemmas for physicians. This may be related, in part, to the fact that these lesions represent a range of diagnostic possibilities, from inflammatory cysts and nonmucinous cysts to mucinous cysts, which may or may not have foci of invasive malignancy. Adequate characterization of cystic lesions is necessary to help devise a management plan. Moreover, patient-related factors such as comorbid conditions are often essential in deciding whether patients should be managed by a conservative approach of watchful waiting versus surgical resection, if so indicated. This review summarizes the recent advances in the management of pancreatic cystic neoplasms.

Personalizing pancreatic cancer medicine: what are the challenges?

The P4 paradigm for future medicine promises changes in cancer management with improved Prediction of treatment response, Prevention of disease, Personalization of therapy, and Participation by patients. Significant challenges remain for the implementation of the P4 principles for pancreatic cancer, but many strides have been made in the past several years that should facilitate a future in which the disease can be detected at earlier stages and treatments can be customized to target features of a particular patient’s disease. This article summarizes the basic molecular biology of pancreatic tumors and the current state of pancreatic cancer treatment, as well as targeted treatments in the pipeline that might enable future personalized pancreatic cancer treatment and prediction of response to treatment. It also discusses possible directions for screening patients at high risk of developing the disease, detecting tumors at earlier stages, and increasing patient involvement in designing treatment.

Comparison of surgical and endoscopic sample collection for pancreatic cyst fluid biomarker identification

Significant efforts are underway to develop new biomarkers from pancreatic cyst fluid. Previous research has made use of cyst fluid collected from surgically removed cysts, but the clinical implementation of biomarkers would use cyst fluid collected by endoscopic ultrasound-guided, fine-needle aspiration (EUS-FNA). The purpose of this study was to investigate the clinical applicability of cyst fluid research obtained using surgical specimens. Matched pairs of operating-room collected (OR) and EUS-FNA samples from 12 patients were evaluated for the levels of three previously described biomarkers, CA 19-9, CEA, and glycan levels detected by wheat germ agglutinin on MUC5AC (MUC5AC-WGA). CA 19-9 and MUC5AC-WGA correlated well between the sample types, although CEA was more variable between the sample types for certain patients. The variability was not due to the time delay between EUS-FNA and OR collection or differences in total protein concentrations but may be caused by contamination of the cyst fluid with blood proteins. The classification of each patient based on thresholds for each marker was perfectly consistent between sample types for CA 19-9 and MUC5AC-WGA and mostly consistent for CEA. Therefore, results obtained using OR-collected pancreatic cyst fluid samples should reliably transfer to the clinical setting using EUS-FNA samples.