Transthyretin, identified by proteomics, is overabundant in pancreatic juice from pancreatic carcinoma and originates from pancreatic islets

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.

Single-Cell Transcriptomic Analysis of the Mouse Pancreas: Characteristic Features of Pancreatic Ductal Cells in Chronic Pancreatitis

Chronic pancreatitis (CP) is a fibroinflammatory disorder of the pancreas. Our understanding of CP pathogenesis is partly limited by the incomplete characterization of pancreatic cell types. Here, we performed single-cell RNA sequencing on 3825 cells from the pancreas of one control mouse and mice with caerulein-induced CP. An analysis of the single-cell transcriptomes revealed 16 unique clusters and cell type-specific gene expression patterns in the mouse pancreas. Sub-clustering of the pancreatic mesenchymal cells from the control mouse revealed four clusters of cells with specific gene expression profiles (combinatorial expressions of Smoc2, Cxcl14, Tnfaip6, and Fn1). We observed that immune cells in the pancreas of the CP mice were abundant and diverse in cellular type. Compared to the control, 547 upregulated genes (including Mmp7, Ttr, Rgs5, Adh1, and Cldn2) and 257 downregulated genes were identified in ductal cells from the CP group. The elevated expression levels of MMP7 and TTR were further verified in the pancreatic ducts of CP patients. This study provides a preliminary description of the single-cell transcriptome profiles of mouse pancreata and accurately demonstrates the characteristics of pancreatic ductal cells in CP. The findings provide insight into novel disease-specific biomarkers and potential therapeutic targets of CP.

Simple Serum Pancreatic Ductal Adenocarcinoma (PDAC) Protein Biomarkers-Is There Anything in Sight?

A poor PDAC prognosis is due to a lack of effective treatment and late diagnosis. The early detection of PDAC could significantly decrease mortality and save lives. Idealbiomarkers for PDAC should be cost-effective, detectable in easily accessible biological material, and present in sufficient concentration in the earliest possible phase of the disease. This review addresses newly selected, simple protein biomarkers—new ones such as thrombospondin-2, insulin-linked binding protein 2, lysophosphatidic acid, and autotaxin and conventional ones such as Ca19-9, inflammatory factors, and coagulation factors. Their possible use in the early detection of PDAC, differentiation from benign diseases, prognosis, and treatment response prediction is discussed. We also address the usefulness of possible combinations of biomarkers in diagnostic panels.

Current State of "Omics" Biomarkers in Pancreatic Cancer

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different "omics" levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.

Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients

Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody production and can be PDA theranostic targets. However, the prognostic value of TAA-antibody association as Circulating Immune Complexes (CIC) has not yet been elucidated, mainly due to the lack of techniques that lead to their identification. In this study, we show a novel method to separate IgG, IgM, and IgA CIC from sera to use them as prognostic biomarkers of CT response. The PDA Immune-Complexome (IC) was identified using a LTQ-Orbitrap mass spectrometer followed by computational analysis. The analysis of the IC of 37 PDA patients before and after CT revealed differential associated antigens (DAA) for each immunoglobulin class. Our method identified different PDA-specific CIC in patients that were associated with poor prognosis patients. Finally, CIC levels were significantly modified by CT suggesting that they can be used as effective prognostic biomarkers to follow CT response in PDA patients.

Diagnostic performance enhancement of pancreatic cancer using proteomic multimarker panel

Due to its high mortality rate and asymptomatic nature, early detection rates of pancreatic ductal adenocarcinoma (PDAC) remain poor. We measured 1000 biomarker candidates in 134 clinical plasma samples by multiple reaction monitoring-mass spectrometry (MRM-MS). Differentially abundant proteins were assembled into a multimarker panel from a training set (n=684) and validated in independent set (n=318) from five centers. The level of panel proteins was also confirmed by immunoassays. The panel including leucine-rich alpha-2 glycoprotein (LRG1), transthyretin (TTR), and CA19-9 had a sensitivity of 82.5% and a specificity of 92.1%. The triple-marker panel exceeded the diagnostic performance of CA19-9 by more than 10% (AUC_CA19-9 = 0.826, AUC_panel= 0.931, P < 0.01) in all PDAC samples and by more than 30% (AUC_CA19-9 = 0.520, AUC_panel = 0.830, P < 0.001) in patients with normal range of CA19-9 (<37U/mL). Further, it differentiated PDAC from benign pancreatic disease (AUC_CA19-9 = 0.812, AUC_panel = 0.892, P < 0.01) and other cancers (AUC_CA19-9 = 0.796, AUC_panel = 0.899, P < 0.001). Overall, the multimarker panel that we have developed and validated in large-scale samples by MRM-MS and immunoassay has clinical applicability in the early detection of PDAC.

[Cystic pancreatic tumors: diagnostics and new biomarkers]

Mortality due to pancreatic ductal adenocarcinoma (PDAC) will increase in the near future. The only curative treatment for PDAC is radical resection; however, even small carcinomas exhibit micrometastases leading to early relapse. Accordingly, detection of premalignant precursor lesions is important. In essence, PDAC develops from three precursor lesions: pancreatic intraepithelial lesions (PanIN), intraductal papillary-mucinous neoplasia (IPMN) and mucinous-cystic neoplasia (MCN). Together with serous cystic neoplasia (SCN) and solid pseudopapillary neoplasia (SPN), these cystic lesions constitute the most common cystic neoplasms in the pancreas. In the case of IPMN, main and branch duct IPMN have to be differentiated because of a markedly different malignancy potential. While main duct IPMN and MCN have a high malignancy transformation rate, branch duct IPMNs are more variable with respect to malignant transformation. This shows that differential diagnosis of cystic lesions is important; however, this is often very difficult to accomplish using conventional imaging. Novel biomarkers and diagnostic tools based on the molecular differences of cystic pancreatic lesions could be helpful to differentiate these lesions and facilitate early diagnosis. The aim is to distinguish the premalignant cysts from strictly benign cystic lesions and a timely detection of malignant transformation. This article provides an overview on the molecular characteristics of cystic pancreatic lesions as a basis for improved diagnostics and the development of new biomarkers.

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.

Transthyretin as a novel candidate biomarker for preeclampsia

Preeclampsia (PE) is considered to be a potentially fatal complication during pregnancy. However, no effective laboratory assessment has been developed to enable early diagnosis and monitoring of PE. The present study aimed to identify differentially expressed transthyretin (TTR) during severe PE and evaluate TTR as a possible biomarker of this disease. TTR levels were determined in the different gestational weeks of normal pregnancy (before 20 weeks, n=41; after 20 weeks, n=39) using enzyme-linked immunosorbent assay (ELISA). TTR concentrations in pregnant females with severe PE (n=43) were compared with those in healthy matched control subjects (n=37) using western blot analysis and ELISA. The median TTR concentration during severe PE in each month of gestation was significantly lower than the concentrations recorded during normal pregnancy. TTR levels in females with severe PE were significantly downregulated compared with the control subjects (P<0.001; area under the curve, 0.834-0.967). Thus, TTR may be used as a potential biomarker of PE.

Validation of four candidate pancreatic cancer serological biomarkers that improve the performance of CA19.9

Background

The identification of new serum biomarkers with high sensitivity and specificity is an important priority in pancreatic cancer research. Through an extensive proteomics analysis of pancreatic cancer cell lines and pancreatic juice, we previously generated a list of candidate pancreatic cancer biomarkers. The present study details further validation of four of our previously identified candidates: regenerating islet-derived 1 beta (REG1B), syncollin (SYCN), anterior gradient homolog 2 protein (AGR2), and lysyl oxidase-like 2 (LOXL2).

Methods

The candidate biomarkers were validated using enzyme-linked immunosorbent assays in two sample sets of serum/plasma comprising a total of 432 samples (Sample Set A: pancreatic ductal adenocarcinoma (PDAC, n = 100), healthy (n = 92); Sample Set B: PDAC (n = 82), benign (n = 41), disease-free (n = 47), other cancers (n = 70)). Biomarker performance in distinguishing PDAC from each control group was assessed individually in the two sample sets. Subsequently, multiparametric modeling was applied to assess the ability of all possible two and three marker panels in distinguishing PDAC from disease-free controls. The models were generated using sample set B, and then validated in Sample Set A.

Results

Individually, all markers were significantly elevated in PDAC compared to healthy controls in at least one sample set (p ≤ 0.01). SYCN, REG1B and AGR2 were also significantly elevated in PDAC compared to benign controls (p ≤ 0.01), and AGR2 was significantly elevated in PDAC compared to other cancers (p < 0.01). CA19.9 was also assessed. Individually, CA19.9 showed the greatest area under the curve (AUC) in receiver operating characteristic (ROC) analysis when compared to the tested candidates; however when analyzed in combination, three panels (CA19.9 + REG1B (AUC of 0.88), CA19.9 + SYCN + REG1B (AUC of 0.87) and CA19.9 + AGR2 + REG1B (AUC of 0.87)) showed an AUC that was significantly greater (p < 0.05) than that of CA19.9 alone (AUC of 0.82). In a comparison of early-stage (Stage I-II) PDAC to disease free controls, the combination of SYCN + REG1B + CA19.9 showed the greatest AUC in both sample sets, (AUC of 0.87 and 0.92 in Sets A and B, respectively).

Conclusions

Additional serum biomarkers, particularly SYCN and REG1B, when combined with CA19.9, show promise as improved diagnostic indicators of pancreatic cancer, which therefore warrants further validation.

Identification and verification of transthyretin as a potential biomarker for pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers worldwide and is difficult to detect at its early stages when treatment is most effective. Therefore, we performed a comparative proteomic study to identify new biomarkers for the detection of PDAC.

METHODS

Serum samples from patients with PDAC, chronic pancreatitis and normal controls were compared using two-dimensional difference gel electrophoresis (2D-DIGE). Differentially expressed separated proteins were subsequently identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/TOF-MS). Then, transthyretin (TTR), one of the differentially expressed proteins, was validated through real-time PCR, western blot and immunohistochemistry. Finally, enzyme-linked immunosorbent assays (ELISA) were employed to confirm the levels of transthyretin in the sera.

RESULTS

A total of 21 protein spots showed greater than 1.5-fold changes in expression level in the sera from PDAC patients compared with the normal controls. Among the identified proteins, validation experiments verified the differential expression of transthyretin in PDAC tissue, confirming the proteomic data showing that transthyretin was significantly elevated in patients with PDAC. The ELISA results revealed that the sensitivity and specificity for TTR and CA19-9 in distinguishing PDAC patients from normal individuals were 90.5, 47.6, 66.7 and 85.7 %, respectively, and 81.0 and 85.7 % for their combination.

CONCLUSIONS

These results suggest that the level of transthyretin is elevated in patients with PDAC. In combination with CA19-9, transthyretin may provide additional information for the detection of PDAC and should be further investigated.

Advances in proteomics of digestive juices for the diagnosis of digestive system malignancies

Body fluid proteomic analysis is a new technology and strategy for disease diagnosis and treatment. Blood is the most commonly used specimen in body fluid proteomics, but as a systemic fluid, it has limitations because of complex composition and low abundance of disease-related proteins. In contrast, local body fluids are closest to the lesions, contain more pathological information, and therefore are more valuable in clinical proteomics. In the digestive system, there are a variety of body fluids which are considered potential reservoirs of biomarkers for their quality and quantity of proteins will alter during lesions occurring in corresponding organs. In recent years, more and more clinical proteomic analyses of saliva, gastric juice, bile and pancreatic juice has been reported and the proteins related to digestive cancers have been found, and some proteins show application potentials in cancer diagnosis. However, the proteomic analyses of digestive juices are facing technical challenges in terms of the reproducibility of results and standardization of specimen handling.

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.