Strategies for discovering novel pancreatic cancer biomarkers

Incorporation of explainable artificial intelligence in ensemble machine learning-driven pancreatic cancer diagnosis

Despite the strides made in medical science, pancreatic cancer continues to be a threat, highlighting the urgent need for creative strategies to address this concern. Recently, a potential approach that has attracted significant attention is using machine learning in clinical decision-making. This research aims to analyze six machine learning algorithms, and an ensemble voting classifier, develop hybrid models for the early detection of pancreatic cancer based on several clinical characteristics and interpret their performance with Shapley Additive Explanations (SHAP). A publicly available dataset composed of 590 patient urine samples was utilized to develop six conventional models for the classification of cancerous from non-cancerous pancreatic cases through the analysis of specific attributes. An ensemble voting classifier was developed from the best-performed single models, which were later hybridized to form six novel hybrid models. The ensemble voting classifier outperformed all stand-alone models with an accuracy of 96.61% and a precision of 98.72%. The six novel hybrid models exhibited higher performance than single models with voting classifier random forest hybridized model outperforming others with an AUC of 99.05% (95% confidence interval (CI): 0.93-1.00) and an interpretation was given by SHAP showing top influential features in pancreatic cancer diagnosis that exhibited the greatest positive SHAP values. Employing rapid sophisticated models with high accuracy and precision holds significant promise in facilitating the effective detection of various diseases, including pancreatic cancer.

Metabolomic Approach to Identify Potential Biomarkers in KRAS-Mutant Pancreatic Cancer Cells

Pancreatic cancer is characterized by its high mortality rate and limited treatment options, often driven by oncogenic RAS mutations. In this study, we investigated the metabolomic profiles of pancreatic cancer cells based on their KRAS genetic status. Utilizing both KRAS-wildtype BxPC3 and KRAS-mutant PANC1 cell lines, we identified 195 metabolites differentially altered by KRAS status through untargeted metabolomics. Principal component analysis and hierarchical condition trees revealed distinct separation between KRAS-wildtype and KRAS-mutant cells. Metabolite set enrichment analysis highlighted significant pathways such as homocysteine degradation and taurine and hypotaurine metabolism. Additionally, lipid enrichment analysis identified pathways including fatty acyl glycosides and sphingoid bases. Mapping of identified metabolites to KEGG pathways identified nine significant metabolic pathways associated with KRAS status, indicating diverse metabolic alterations in pancreatic cancer cells. Furthermore, we explored the impact of TRPML1 inhibition on the metabolomic profile of KRAS-mutant pancreatic cancer cells. TRPML1 inhibition using ML-SI1 significantly altered the metabolomic profile, leading to distinct separation between vehicle-treated and ML-SI1-treated PANC1 cells. Metabolite set enrichment analysis revealed enriched pathways such as arginine and proline metabolism, and mapping to KEGG pathways identified 17 significant metabolic pathways associated with TRPML1 inhibition. Interestingly, some metabolites identified in PANC1 compared to BxPC3 were oppositely regulated by TRPML1 inhibition, suggesting their potential as biomarkers for KRAS-mutant cancer cells. Overall, our findings shed light on the distinct metabolite changes induced by both KRAS status and TRPML1 inhibition in pancreatic cancer cells, providing insights into potential therapeutic targets and biomarkers for this deadly disease.

Exploring the Associations of Inflammatory and Oxidative Stress Biomarkers with Pancreatic Diseases: An Observational and Mendelian Randomisation Study

Identifying biomarkers linked to pancreatic ductal adenocarcinoma (PDAC) and chronic pancreatitis (CP) is crucial for early detection, treatment, and prevention. Methods: Association analyses of 10 serological biomarkers involved in cell signalling (IFN-γ, IL-6, IL-8, IL-10), oxidative stress (superoxide dismutase (SOD) and glutathione peroxidase (GPx) enzyme activities, total glutathione (GSH), malondialdehyde (MDA) levels), and intestinal permeability proteins (zonulin, I-FABP2) were conducted across PDAC (n = 12), CP (n = 21) and control subjects (n = 23). A Mendelian randomisation (MR) approach was used to assess causality of the identified significant associations in two large genetic cohorts (FinnGen and UK Biobank). Results: Observational results showed a downregulation of SOD and GPx antioxidant enzyme activities in PDAC and CP patients, respectively, and higher MDA levels in CP patients. Logistic regression models revealed significant associations between CP and SOD activity (OR = 0.21, 95% CI [0.05, 0.89], per SD), GPx activity (OR = 0.28, 95% CI [0.10, 0.79], per SD), and MDA levels (OR = 2.05, 95% CI [1.36, 3.08], per SD). MR analyses, however, did not support causality. Conclusions: These findings would not support oxidative stress-related biomarkers as potential targets for pancreatic diseases prevention. Yet, further research is encouraged to assess their viability as non-invasive tools for early diagnosis, particularly in pre-diagnostic CP populations.

The Gut Microbiome and Pancreatic Cancer Development and Treatment

ABSTRACT

Changes in the gut microbiome have been increasingly shown to accompany oncogenesis across various tumors. Similarly, microbial dysbiosis was found to be associated with pancreatic cancer progression and survival outcomes, expanding the field of tumor microenvironment research in pancreatic cancer. Mechanistic studies in pancreatic cancer models implicate components of the gut and pancreatic cancer microbiome in regulating tumorigenesis by altering cancer cell signaling, modulating immune function, and influencing the efficacy of current therapies in pancreatic cancer. This review discusses the outcomes of microbial modulation across various preclinical and clinical studies and highlights ongoing trials targeting the microbiome for pancreatic cancer therapy.

Characterization of Mesothelin Glycosylation in Pancreatic Cancer: Decreased Core Fucosylated Glycoforms in Pancreatic Cancer Patients’ Sera

Currently, there are no reliable biomarkers for the diagnosis of pancreatic cancer (PaC). Glycoproteomic approaches that analyze the glycan determinants on specific glycoproteins have proven useful to develop more specific cancer biomarkers than the corresponding protein levels. In PaC, mesothelin (MSLN) is a neo-expressed glycoprotein. MSLN glycosylation has not been described and could be altered in PaC. In this work, we aimed to characterize MSLN glycans from PaC cells and serum samples to assess their potential usefulness as PaC biomarkers. First, we analyzed MSLN glycans from PaC cell lines and then we developed an enzyme-linked lectin assay to measure core fucosylated-MSLN (Cf-MSLN) glycoforms. MSLN glycans from PaC cells were analyzed by glycan sequencing and through Western blotting with lectins. All of the cell lines secreted MSLN, with its three N-glycosylation sites occupied by complex-type N-glycans, which were mainly α2,3-sialylated, core fucosylated and highly branched. The Cf-MSLN glycoforms were quantified on PaC serum samples, and compared with MSLN protein levels. The Cf-MSLN was significantly decreased in PaC patients compared to control sera, while no differences were detected by using MSLN protein levels. In conclusion, Cf-MSLN glycoforms were differently expressed in PaC, which opens the way to further investigate their usefulness as PaC biomarkers.

Phaseolus vulgaris Erythroagglutinin (PHA-E)-Positive Ceruloplasmin Acts as a Potential Biomarker in Pancreatic Cancer Diagnosis

Pancreatic cancer (PC) remains one of the top 10 causes of cancer-related death in recent years. Approximately 80% of PC patients are diagnosed at the middle or advanced stage and miss the opportunity for surgery. The demand for early diagnostic methods and reliable biomarkers is increasing, although a number of tumor markers such as CA19-9 and CEA have already been utilized in clinics. In this study, we analyzed the alteration of N-glycan of serum glycoproteins by mass spectrometry and lectin blotting. The results showed that bisecting GlcNAc structures of glycoproteins are significantly increased in PC patients' sera. With Phaseolus vulgaris Erythroagglutinin (PHA-E) lectin that specifically recognizes bisecting GlcNAc N-glycans, the serum glycoproteins bearing bisecting GlcNAc in PC patients' sera were pulled down and identified by nano-LC-MS/MS. Among them, ceruloplasmin (Cp) was screened out with a satisfied sensitivity and specificity in identifying PC from acute pancreatitis patients (AUC: 0.757) and normal healthy persons (AUC: 0.972), suggesting a close association between Cp and PC development and diagnosis. To prove that, the Cp expression in tumor tissues of PC patients was examined. The results showed that Cp was significantly upregulated in PC tissues compared to that in adjacent normal tissues. All these results suggested that PHA-E-positive Cp could be a potential PC-specific glycoprotein marker to distinguish PC patients from acute pancreatitis patients and normal persons.

Multiomic characterization of pancreatic cancer-associated macrophage polarization reveals deregulated metabolic programs driven by the GM-CSF-PI3K pathway

The pancreatic ductal adenocarcinoma microenvironment is composed of a variety of cell types and marked by extensive fibrosis and inflammation. Tumor-associated macrophages (TAMs) are abundant, and they are important mediators of disease progression and invasion. TAMs are polarized in situ to a tumor promoting and immunosuppressive phenotype via cytokine signaling and metabolic crosstalk from malignant epithelial cells and other components of the tumor microenvironment. However, the specific distinguishing features and functions of TAMs remain poorly defined. Here, we generated tumor-educated macrophages (TEMs) in vitro and performed detailed, multiomic characterization (i.e., transcriptomics, proteomics, metabolomics). Our results reveal unique genetic and metabolic signatures of TEMs, the veracity of which were queried against our in-house single-cell RNA sequencing dataset of human pancreatic tumors. This analysis identified expression of novel, metabolic TEM markers in human pancreatic TAMs, including ARG1, ACLY, and TXNIP. We then utilized our TEM model system to study the role of mutant Kras signaling in cancer cells on TEM polarization. This revealed an important role for granulocyte-macrophage colony-stimulating factor (GM-CSF) and lactate on TEM polarization, molecules released from cancer cells in a mutant Kras-dependent manner. Lastly, we demonstrate that GM-CSF dysregulates TEM gene expression and metabolism through PI3K-AKT pathway signaling. Collectively, our results define new markers and programs to classify pancreatic TAMs, how these are engaged by cancer cells, and the precise signaling pathways mediating polarization.

The role of TPS, CA125, CA15-3 and CEA in prediction of distant metastasis of breast cancer

OBJECTIVE

To explore the application value of breast cancer tumor markers tissue polypeptide specific antigen (TPS), carbohydrate antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125) detection alone or in combination for the monitoring of distant metastasis of breast cancer.

METHOD

The clinical data of 389 female breast cancer patients admitted to Tianjin Medical University Cancer Institute and Hospital from January 2016 to March 2017 were retrospectively analyzed. Serum levels of TPS, CA125, CA15-3, and CEA were compared to analyze their significance in prediction distant metastasis of breast cancer. The patients were divided into the distant metastatic group and the non-metastatic group according to whether the patients had distant metastasis. The non-metastatic group was divided into the control group and the occult metastasis group according to whether distant metastases occurred in 3 years after treatment.

RESULT

The receiver operating characteristic curve analysis revealed that all four markers had the diagnostic value in distant metastasis of breast cancer (AUC_TPS = 0.754, AUC_15-3 = 0.821, AUC_CEA = 0.755, AUC_CA125 = 0.651) and in occult metastasis in 3 years after treatment (AUC_TPS = 0.751, AUC_15-3 = 0.744, AUC_CEA = 0.725, AUC_CA125 = 0.661). To estimate whether the discrimination ability could be improved by marker panels, we established marker panels composed of TPS, CA125, CA15-3, and CEA. To discriminate distant metastasis from non-distant metastasis, the diagnostic ability of different panels composed of TPS, CA125, CA15-3 and CEA did not show significant difference compared with single CA15-3 (P > 0.05). To discriminate occult metastasis from the control group, no significant difference was shown in AUC between marker panels and single marker (P > 0.05). However, the sensitivity was improved when the marker-panels were used overall.

CONCLUSION

All tumor markers have abilities in prediction of distant metastasis of breast cancer. The combined detection of the markers is more valuable than using single tumor marker in improving sensitivity. Two markers' panels are more suitable for the prediction of distant metastasis of breast cancer than three or four makers' panels with the similar sensitivity and AUC.

Non-Invasive Biomarkers for Earlier Detection of Pancreatic Cancer-A Comprehensive Review

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 90% of all pancreatic cancers, is an extremely aggressive and lethal disease. It is considered a silent killer due to a largely asymptomatic course and late clinical presentation. Earlier detection of the disease would likely have a great impact on changing the currently poor survival figures for this malignancy. In this comprehensive review, we assessed over 4000 reports on non-invasive PDAC biomarkers in the last decade. Applying the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, we selected and reviewed in more detail 49 relevant studies reporting on the most promising candidate biomarkers. In addition, we also highlight the present challenges and complexities of translating novel biomarkers into clinical use.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010—August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved.

ITGB6 may promote proliferation and invasion in pancreatic cancer

Introduction

The ITGB6 gene encoding a protein that can regulate the integrin αvβ6 heterodimer protein expression in different status was shown to play an important role in multiple human cancers, such as brain cancer, colon cancer and oral cancer, and is related to clinical progression. This study aims to explore the function and the mechanism of the ITGB6 gene or protein in pancreatic cancer.

Material and methods

We examined the expression of ITGB6 in pancreatic cancer using immunohistochemistry and analyzed the relationship between the expression of ITGB6 and the clinicopathologic features in pancreatic cancer patients. In addition, a bioinformatic method was used to analyze the ITGB6 mRNA level in pancreatic tumor tissues compared with normal pancreatic tissues and to analyze the correlation between high KIF23 expression and prognosis in pancreatic cancer patients. Moreover, colony formation assay, MTT assay, cell scratch, cell invasion and western blot assays in vitro and a xenograft mouse model in vivo were performed to analyze the effect of KIF23 on proliferation and invasion of pancreatic cancer cells.

Results

Increased expression of ITGB6 was significantly correlated with poor clinical outcome in both our clinical data and TCGA data of pancreatic cancer. Furthermore, functional assays revealed that ITGB6 knockdown in vivo and in vitro might inhibit cancer cell proliferation and the ability of invasion or migration.

Conclusions

Our data suggest that ITGB6 is associated with pancreatic cancer malignant progression. Hence, ITGB6 may serve as a potential target of pancreatic cancer for future research, and further study is needed.

A novel lncRNA PTTG3P/miR-132/212-3p/FoxM1 feedback loop facilitates tumorigenesis and metastasis of pancreatic cancer

Pseudogene pituitary tumor-transforming 3 (PTTG3P) is emerging as a key player in the development and progression of cancer. However, the biological role and clinical significance of PTTG3P in pancreatic ductal adenocarcinoma (PDAC) remain unclear. Here, we found that PTTG3P was significantly upregulated in PDAC tissues. Elevated PTTG3P expression correlated with larger tumor size and worse differentiation, and reduced overall survival. Bioinformatics and experimental evidence revealed that PTTG3P promoted malignant phenotypes and FoxM1 signaling pathway in PDAC cells. Mechanistically, PTTG3P functions as a microRNA sponge to positively regulate the expression of FoxM1 through sponging miR-132/212-3p. Moreover, it showed that FoxM1 transcriptionally activated PTTG3P expression, thus forming a feedback loop to promote the aggressiveness of PDAC cells. Taken together, our findings suggest that PTTG3P promotes PDAC progression through PTTG3P/miR-132/212-3p/FoxM1 feedforward circuitry and it may serve as a promising diagnostic marker or target for treatment in PDAC patients.

Microfibril associated protein 4 (MFAP4) is a carrier of the tumor associated carbohydrate sialyl-Lewis x (sLex) in pancreatic adenocarcinoma

Late diagnosis of pancreatic ductal adenocarcinoma (PDA) is one of the reasons of its low 5-year survival rate and it is due to its unspecific symptoms during the first stages of the disease and the lack of reliable serological markers. Since PDA shows an altered glycan expression, here we have focused on finding novel potential biomarkers, namely glycoproteins that express the tumor associated carbohydrate structure sialyl-Lewis x (sLe^x), which is described in PDA. Through a glycoproteomic approach, we have analyzed target proteins containing sLe^x from PDA tissues by 2DE and immunodetection techniques, and have identified by mass spectrometry the protein MFAP4 as a carrier of sLe^x in PDA. MFAP4 showed a higher expression in PDA tissues compared with pancreatic control tissues. In addition, the colocalization of sLe^x over MFAP4 was found only in PDA and not in control pancreatic tissues. The analysis of MFAP4 expression in PDA cell lines and their secretome, in combination with immunohistochemistry of pancreatic tissues, revealed that MFAP4 was not produced by PDA cells, but it was found in the pancreatic extracellular matrix. The specificity of MFAP4 glycoform containing sLe^x in PDA tissues shows its relevance as a potential PDA biomarker. SIGNIFICANCE: Despite advances in the field of cancer research, pancreatic ductal adenocarcinoma (PDA) lacks of a specific and sensitive biomarker for its early detection, when curative resection is still possible before metastases arise. Thus, efforts to discover new PDA biomarkers represent the first line in the fight against the increase of its incidence reported in recent years. Glycan alterations on glycoconjugates, such as glycoproteins have emerged as a rich source for the identification of novel cancer markers. In the present work, we aimed to shed light on novel biomarkers based on altered glycosylation in PDA, in particular those glycoproteins of PDA tissues carrying the tumor carbohydrate antigen sialyl-Lewis x (sLe^x). Through a glycoproteomic approach, we have shown that the glycoprotein MFAP4 carries sLe^x in PDA tissues and not in control pancreatic tissues. MFAP4 is found in the extracellular matrix in PDA and although its role in cancer progression is unclear, its sLe^x glycoform could be a potential biomarker in pancreatic ductal adenocarcinoma.

Glutathione S-Transferase pi-1 Knockdown Reduces Pancreatic Ductal Adenocarcinoma Growth by Activating Oxidative Stress Response Pathways

Glutathione S-transferase pi-1 (GSTP1) plays an important role in regulating oxidative stress by conjugating glutathione to electrophiles. GSTP1 is overexpressed in breast, colon, lung, and prostate tumors, where it contributes to tumor progression and drug resistance; however, the role of GSTP1 in pancreatic ductal adenocarcinoma (PDAC) is not well understood. Using shRNA, we knocked down GSTP1 expression in three different PDAC cell lines and determined the effect on cell proliferation, cell cycle progression, and reactive oxygen species (ROS) levels. Our results show GSTP1 knockdown reduces PDAC cell growth, prolongs the G0/G1 phase, and elevates ROS in PDAC cells. Furthermore, GSTP1 knockdown results in the increased phosphorylation of c-Jun N-terminal kinase (JNK) and c-Jun and the decreased phosphorylation of extracellular signal-regulated kinase (ERK), p65, the reduced expression of specificity protein 1 (Sp1), and the increased expression of apoptosis-promoting genes. The addition of the antioxidant glutathione restored cell viability and returned protein expression levels to those found in control cells. Collectively, these data support the working hypothesis that the loss of GSTP1 elevates oxidative stress, which alters mitogen-activated protein (MAP) kinases and NF-κB signaling, and induces apoptosis. In support of these in vitro data, nude mice bearing orthotopically implanted GSTP1-knockdown PDAC cells showed an impressive reduction in the size and weight of tumors compared to the controls. Additionally, we observed reduced levels of Ki-67 and increased expression of cleaved caspase-3 in GSTP1-knockdown tumors, suggesting GSTP1 knockdown impedes proliferation and upregulates apoptosis in PDAC cells. Together, these results indicate that GSTP1 plays a significant role in PDAC cell growth and provides support for the pursuit of GSTP1 inhibitors as therapeutic agents for PDAC.

An Immunosensor for the Detection of ULBP2 Biomarker

Pancreatic cancer (PC) is a global health problem that features a very high mortality rate. The UL16 binding protein 2 (ULBP2) is a new biomarker for PC detection. This study develops a simple, reliable, and inexpensive immunosensor for the detection of the ULBP2 antigen while also investigating the effects of an array configuration of connected sensors and zinc oxide (ZnO) nanoparticles on the immunosensor’s sensitivity. The ULBP2 antibody was immobilized onto the screen-printed carbon electrode (SPCE) surfaces of three different sensors: a simple SPCE (ULBP2-SPCE); an SPCE array, which is a series of identical SPCE connected to each other at different arrangements of rows and columns (ULBP2-SPCE-1x2 and ULBP2-SPCE-1x3); and an SPCE combined with ZnO nanoparticles (ULBP2-ZnO/SPCE). Impedance spectrum measurements for the immunosensors to ULBP2 antigen were conducted and compared. According to the result, the array configurations (ULBP2-SPCE-1x2 and ULBP2-SPCE-1x3) show an improvement of sensitivity compared to the ULBP2-SPCE alone, but the improvement is not as significant as that of the ULBP2-ZnO/SPCE configuration (ULBP2-ZnO/SPCE > ULBP2-SPCE: 18 times larger). The ULBP2-ZnO/SPCE immunosensor has a low limit of detection (1 pg/mL) and a high sensitivity (332.2 Ω/Log(pg/mL)), excellent linearity (R² = 0.98), good repeatability (coefficients of variation = 5.03%), and is stable in long-term storage (retaining 95% activity after 28 days storage). In an array configuration, the immunosensor has an increased signal-to-noise ratio (ULBP2-SPCE-1x3 > ULBP2-SPCE: 1.5-fold) and sensitivity (ULBP2-SPCE-1x3 > ULBP2-SPCE: 2.6-fold). In conclusion, either the modification with ZnO nanoparticles onto the sensor or the use of an array configuration of sensors can enhance the immunosensor’s sensitivity. In this study, the best immunosensor for detecting ULBP2 antigens is the ULBP2-ZnO/SPCE immunosensor.

Proteostasis Dysregulation in Pancreatic Cancer

The most common form of pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC), has a dismal 5-year survival rate of less than 5%. Radical surgical resection, in combination with adjuvant chemotherapy, provides the best option for long-term patient survival. However, only approximately 20% of patients are resectable at the time of diagnosis, due to locally advanced or metastatic disease. There is an urgent need for the identification of new, specific, and more sensitive biomarkers for diagnosis, prognosis, and prediction to improve the treatment options for pancreatic cancer patients. Dysregulation of proteostasis is linked to many pathophysiological conditions, including various types of cancer. In this review, we report on findings relating to the main cellular protein degradation systems, the ubiquitin-proteasome system (UPS) and autophagy, in pancreatic cancer. The expression of several components of the proteolytic network, including E3 ubiquitin-ligases and deubiquitinating enzymes, are dysregulated in PDAC, which accounts for approximately 90% of all pancreatic malignancies. In the future, a deeper understanding of the emerging role of proteostasis in pancreatic cancer has the potential to provide clinically relevant biomarkers and new strategies for combinatorial therapeutic options to better help treat the patients.

Magnetized Carbon Nanotube Based Lateral Flow Immunoassay for Visual Detection of Complement Factor B

The authors describe a magnetized carbon nanotube (MCNT) based lateral flow immunoassay (LFI) for visual detection of complement factor B (CFB) in blood. MCNT was prepared by decorating magnetic Fe₃O₄ nanoparticles on multi-walled CNT surface and used as a colored tag for LFI. Monoclonal antibody (mAb, Ab₁) of CFB was covalently immobilized on the MCNT surface via diimide-activated conjugation between the carboxyl groups on the MCNT surface and amino groups of antibodies. Polyclonal antibody of CFB (Ab₂) and the secondary antibody were used to prepare the lateral flow test strips. The assay involved: (1) the capture of CFB in blood with the mAb-functionalized MCNT; (2) magnetic separation of the formed CFB-mAb-MCNT and excess of mAb-MCNT from the blood with an external magnet; (3) lateral flow test to capture the CFB-mAb-MCNT complex on the test zone and the excess of mAb-MCNT on the control zone; (4) Recording the intensities of the produced the characteristic brown bands with a portable strip reader and quantitating the concentration of CFB. The proof-of-concept was demonstrated by testing CFB in the buffer, and the detection limit was 5 ng mL^-1 under the optimized analytical parameters. CFB in 1 μL of human blood was detected successfully in 30 min with this LFI and the results had a high correlation with commercial ELISA kit. Thence, the MCNT-based LFI offers a rapid and low-cost tool for detecting CFB in human blood directly.

RNA-Binding Motif Protein 6 is a Candidate Serum Biomarker for Pancreatic Cancer

PURPOSE

Early diagnosis is crucial to improve outcomes for pancreatic cancer patients (PC). The present study is designed to identify differently expressed peptides involved in PC as potential biomarkers.

EXPERIMENTAL DESIGN

The serum proteome of 22 PC patients, 12 pancreatitis patients (PP), and 45 healthy controls (HC) are analyzed using magnetic bead-based weak cation exchange (MB-WCX) and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Next, a supervised neural network (SNN) algorithm model is established by ClinProTools and the candidate biomarker identified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Finally, the candidate biomarker is validated in tissue samples.

RESULTS

The SNN algorithm model discriminates PC from HC with 92.97% sensitivity and 94.55% specificity. Seventy-six differentially expressed peptides are identified, seven of which are significantly different among PC, PP, and HC (p < 0.05). Only one peak (m/z: 1466.99) tends to be upregulated in samples from HC, PP, and PC, which is identified as region of RNA-binding motif protein 6 (RBM6). In subsequent tissue analysis, it is verified that RBM6 expression is significantly higher in PC tissues than paracancerous tissue.

CONCLUSIONS AND CLINICAL RELEVANCE

The results indicate that RBM6 might serve as a candidate diagnostic biomarker for PC.

CLINICAL RELEVANCE

Methods used in this study could generate serum peptidome profiles of PC, PP, and HC, and present an approach to identify potential biomarkers for diagnosis of this malignancy.

Transforming growth factor beta-induced, an extracellular matrix interacting protein, enhances glycolysis and promotes pancreatic cancer cell migration

Pancreatic ductal adenocarcinoma (PDAC) remains a deadly malignancy with no efficient therapy available up-to-date. Glycolysis is the main provider of energetic substrates to sustain cancer dissemination of PDAC. Accordingly, altering the glycolytic pathway is foreseen as a sound approach to trigger pancreatic cancer regression. Here, we show for the first time that high transforming growth factor beta-induced (TGFBI) expression in PDAC patients is associated with a poor outcome. We demonstrate that, although usually secreted by stromal cells, PDAC cells synthesize and secrete TGFBI in quantity correlated with their migratory capacity. Mechanistically, we show that TGFBI activates focal adhesion kinase signaling pathway through its binding to integrin αVβ5, leading to a significant enhancement of glycolysis and to the acquisition of an invasive phenotype. Finally, we show that TGFBI silencing significantly inhibits PDAC tumor development in a chick chorioallantoic membrane assay model. Our study highlights TGFBI as an oncogenic extracellular matrix interacting protein that bears the potential to serve as a target for new anti-PDAC therapeutic strategies.

Integrative Analysis of Novel Metabolic Subtypes in Pancreatic Cancer Fosters New Prognostic Biomarkers

Background: Most of the patients with Pancreatic Ductal Adenocarcinoma (PDA) are not eligible for a curative surgical resection. For this reason there is an urgent need for personalized therapies. PDA is the result of complex interactions between tumor molecular profile and metabolites produced by its microenvironment. Despite recent studies identified PDA molecular subtypes, its metabolic classification is still lacking. Methods: We applied an integrative analysis on transcriptomic and genomic data of glycolytic genes in PDA. Data were collected from public datasets and molecular glycolytic subtypes were defined using hierarchical clustering. The grade of purity of the cancer samples was assessed estimating the different amount of stromal and immunological infiltrate among the identified PDA subtypes. Analyses of metabolomic data from a subset of PDA cell lines allowed us to identify the different metabolites produced by the metabolic subtypes. Sera of a cohort of 31 PDA patients were analyzed using Q-TOF mass spectrometer to measure the amount of metabolic circulating proteins present before and after chemotherapy. Results: Our integrative analysis of glycolytic genes identified two glycolytic and two non-glycolytic metabolic PDA subtypes. Glycolytic patients develop disease earlier, have poor prognosis, low immune-infiltrated tumors, and are characterized by a gain in chr12p13 genomic region. This gain results in the over-expression of GAPDH, TPI1, and FOXM1. PDA cell lines with the gain of chr12p13 are characterized by an higher lipid uptake and sensitivity to drug targeting the fatty acid metabolism. Our sera proteomic analysis confirms that TPI1 serum levels increase in poor prognosis gemcitabine-treated patients. Conclusions: We identify four metabolic PDA subtypes with different prognosis outcomes which may have pivotal role in setting personalized treatments. Moreover, our data suggest TPI1 as putative prognostic PDA biomarker.

Periostin and CA242 as potential diagnostic serum biomarkers complementing CA19.9 in detecting pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with few biomarkers to guide treatment options. Carbohydrate antigen 19.9 (CA19.9), the most frequently used biomarker for PDAC, is not sensitive and specific enough for the detection of the disease. This study aimed to evaluate serum periostin (POSTN) and CA242 as potential diagnostic biomarkers complementing CA19.9 in detecting pancreatic cancer. Blood samples were from 362 participants, including 213 patients with different stages of PDAC, 75 patients with benign pancreatic disease, and 74 healthy individuals. All samples were randomly divided into a training set and a validation set. Carbohydrate antigen 19.9, CA242, POSTN, as well as carcinoembryonic antigen, were measured by ELISA or automated immunoassay. The receiver operating characteristic curve analysis revealed that the performance of CA19.9 in the validation group were improved by the marker panel composed of CA19.9, POSTN, and CA242, to discriminate early stage PDAC not only from healthy controls (area under the curve [AUC]CA19.9 = 0.94 vs AUCCA19.9 + POSTN + CA242 = 0.98, P < .05) but also from benign conditions (AUCCA19.9 = 0.87 vs AUCCA19.9 + POSTN + CA242 = 0.90, P < .05). In addition, POSTN retained significant diagnostic capabilities to distinguish PDAC CA19.9-negative from healthy controls (AUCPOSTN = 0.87) as well as from benign conditions (AUCPOSTN = 0.84) in the whole set. This study suggested that POSTN and CA242 are potential diagnostic serum biomarkers complementing CA19.9 in detecting early pancreatic cancer.

A systematic review on metabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer

INTRODUCTION

Metabolomics is an emerging approach for early detection of cancer. Along with the development of metabolomics, high-throughput technologies and statistical learning, the integration of multiple biomarkers has significantly improved clinical diagnosis and management for patients.

OBJECTIVES

In this study, we conducted a systematic review to examine recent advancements in the oncometabolomics-based diagnostic biomarker discovery and validation in pancreatic cancer.

METHODS

PubMed, Scopus, and Web of Science were searched for relevant studies published before September 2017. We examined the study designs, the metabolomics approaches, and the reporting methodological quality following PRISMA statement. RESULTS AND CONCLUSION: The included 25 studies primarily focused on the identification rather than the validation of predictive capacity of potential biomarkers. The sample size ranged from 10 to 8760. External validation of the biomarker panels was observed in nine studies. The diagnostic area under the curve ranged from 0.68 to 1.00 (sensitivity: 0.43-1.00, specificity: 0.73-1.00). The effects of patients' bio-parameters on metabolome alterations in a context-dependent manner have not been thoroughly elucidated. The most reported candidates were glutamic acid and histidine in seven studies, and glutamine and isoleucine in five studies, leading to the predominant enrichment of amino acid-related pathways. Notably, 46 metabolites were estimated in at least two studies. Specific challenges and potential pitfalls to provide better insights into future research directions were thoroughly discussed. Our investigation suggests that metabolomics is a robust approach that will improve the diagnostic assessment of pancreatic cancer. Further studies are warranted to validate their validity in multi-clinical settings.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Proteomic biomarkers in body fluids associated with pancreatic cancer

Pancreatic cancer (PC) is a highly malignant disease that represents the fourth leading cancer-related death worldwide. There has been very little improvement in survival rates over recent years, and surgical resection remains the only reliable curative approach. Factors that contribute to this dismal prognosis for PC include its rapid progression and invasion, the absence of specific symptoms, and the little impact of available chemotherapy. Importantly, the management of this malignancy is also limited by the lack of highly specific and sensitive biomarkers for its diagnosis and follow-up, and their identification is therefore considered a promising strategy to improve outcomes in these patients. Numerous translational studies have explored the usefulness of body fluids as a non-invasive source of PC-specific biomarkers, and innovations in proteomic methods and technologies have provided a myriad of protein biomarkers for different cancers. The adoption of a proteomic approach has improved understanding of the biology of PC and contributed to the potential identification of protein biomarkers for this disease. This review considers the most recent research efforts to develop novel proteomic biomarkers in body fluids for PC.

Ratiometric Fluorescence Detection of Phosphorylated Amino Acids Through Excited-State Proton Transfer by Using Molecularly Imprinted Polymer (MIP) Recognition Nanolayers

A 2,3-diaminophenazine bis-urea fluorescent probe monomer (1) was developed. It responds to phenylphosphate and phosphorylated amino acids in a ratiometric fashion with enhanced fluorescence accompanied by the development of a redshifted emission band arising from an excited-state proton transfer (ESPT) process in the hydrogen-bonded probe/analyte complex. The two urea groups of 1 form a cleft-like binding pocket (K_b >10¹⁰  L²  mol^-2 for 1:2 complex). Imprinting of 1 in presence of ethyl ester- and fluorenylmethyloxycarbonyl (Fmoc)-protected phosphorylated tyrosine (Fmoc-pTyr-OEt) as the template, methacrylamide as co-monomer, and ethyleneglycol dimethacrylate as cross-linker gave few-nanometer-thick molecularly imprinted polymer (MIP) shells on silica core microparticles with excellent selectivity for the template in a buffered biphasic assay. The supramolecular recognition features were established by spectroscopic and NMR studies. Rational screening of co-monomers and cross-linkers allowed to single out the best performing MIP components, giving significant imprinting factors (IF>3.5) while retaining ESPT emission and the ratiometric response in the thin polymer shell. Combination of the bead-based detection scheme with the phase-transfer assay dramatically improved the IF to 15.9, allowing sensitive determination of the analyte directly in aqueous media.

Circulating exosomes and exosomal microRNAs as biomarkers in gastrointestinal cancer

The most important biological function of exosomes is their possible use as biomarkers in clinical diagnosis. Compared with biomarkers identified in conventional specimens such as serum or urine, exosomal biomarkers provide the highest amount of sensitivity and specificity, which can be attributed to their excellent stability. Exosomes, which harbor different types of proteins, nucleic acids and lipids, are present in almost all bodily fluids. The molecular constituents of exosomes, especially exosomal proteins and microRNAs (miRNAs), are promising as biomarkers in clinical diagnosis. This discovery that exosomes also contain messenger RNAs and miRNAs shows that they could be carriers of genetic information. Although the majority of RNAs found in exosomes are degraded RNA fragments with a length of <200 nucleotides, some full-length RNAs might be present that may affect protein production in the recipient cell. In addition, exosomal miRNAs have been found to be associated with certain diseases. Several studies have pointed out miRNA contents of circulating exosomes that are similar to those of originating cancer cells. In this review, the recent advances in circulating exosomal miRNAs as biomarkers in gastrointestinal cancers are discussed. These studies indicated that miRNAs can be detected in exosomes isolated from body fluids such as saliva, which suggests potential advantages of using exosomal miRNAs as noninvasive novel biomarkers.

Employing Metabolism to Improve the Diagnosis and Treatment of Pancreatic Cancer

Pancreatic ductal adenocarcinoma is on pace to become the second leading cause of cancer-related death. The high mortality rate results from a lack of methods for early detection and the inability to successfully treat patients once diagnosed. Pancreatic cancer cells have extensively reprogrammed metabolism, which is driven by oncogene-mediated cell-autonomous pathways, the unique physiology of the tumor microenvironment, and interactions with non-cancer cells. In this review, we discuss how recent efforts delineating rewired metabolic networks in pancreatic cancer have revealed new in-roads to develop detection and treatment strategies for this dreadful disease.

D-dopachrome tautomerase is over-expressed in pancreatic ductal adenocarcinoma and acts cooperatively with macrophage migration inhibitory factor to promote cancer growth

Previous studies have established the important role of MIF in the development of pancreatic ductal adenocarcinoma (PDAC) for both therapeutic and diagnostic perspectives, but little is known about the expression and function of D-dopachrome tautomerase (DDT), a functional homolog of MIF, in PDAC. In the present study, we demonstrated that DDT was over-expressed in PDAC tissues in a pattern correlated with MIF. In the pancreatic cancer cell lines, PANC-1, BXPC-3 and ASPC-1, both DDT and MIF were expressed and co-localized with each other in the endosomal compartments and plasma membrane. Knockdown of DDT and MIF in PANC-1 cells cooperatively inhibited ERK1/2 and AKT phosphorylation, increased p53 expression, and reduced cell proliferation, invasion and tumor formation. These effects were rescued by the re-expression of MIF or DDT, but not by the forced expression of the tautomerase-deficient mutants of DDT and MIF, P1G-DDT and P1G-MIF. Finally, we observed that 4-iodo-6-phenylpyrimidine (4-IPP), a covalent tautomerase inhibitor of both DDT and MIF, attenuated PANC-1 cell proliferation and colony formation in vitro and tumor growth in vivo. Thus, targeting the tautomerase sites of both MIF and DDT may offer more efficient therapeutic benefits to PDAC patients.

Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

Elevated serum CA72-4 levels predict poor prognosis in pancreatic adenocarcinoma after intensity-modulated radiation therapy

Carbohydrate antigen 72-4 (CA72-4) is a human tumor-associated glycoprotein, commonly used as a tumor marker for diagnosing and predicting outcome in gastric and ovarian cancers. However, the relationship between serum CA72-4 levels and prognosis of pancreatic adenocarcinoma has not been fully elucidated. A total of 113 consecutive locally advanced pancreatic adenocarcinoma patients who underwent intensity-modulated radiation therapy (IMRT) with or without chemotherapy were enrolled in this study. Serum CA72-4 levels were analyzed using immunoenzymometric assays. The association between serum CA72-4 levels and prognosis was evaluated. Serum CA72-4 levels was related with lymph node metastasis (P<0.001). The median overall survival time was 14.0 months for patients with serum CA72-4 normal levels and 10.0 months for the elevated levels (P<0.001). Multivariate analysis identified that Serum CA72-4 concentration was a significant prognostic factor (P<0.001). The hazard ratio (HR) of elevated serum CA72-4 levels compared with normal serum CA72-4 levels was 2.34 (95% confidence interval [CI]: 1.46-3.73), after adjusted for gender and age. Based on this finding, Serum CA72-4 is a potential marker to predict lymph node metastasis and prognosis in pancreatic adenocarcinoma.

VNN1, a potential biomarker for pancreatic cancer-associated new-onset diabetes, aggravates paraneoplastic islet dysfunction by increasing oxidative stress

In our previous clinical microarray analysis, we were the first to report on Vanin-1 (VNN1) as a novel clinically derived biomarker of pancreatic cancer-associated new-onset diabetes (PCAND). The functional mechanisms of VNN1 in the pathogenesis of PCAND, however, are not completely understood. In the present study, we further extend our previous clinical study to include laboratory research. The functions and mechanisms of neoplastic overexpressed VNN1 in PCAND have been explored using a co-culture model. Furthermore, the serum concentrations and discrimination power of downstream molecules of VNN1 were tested in a PCAND cohort. Pancreatic ductal adenocarcinoma (PDA) overexpressed VNN1 further aggravates paraneoplastic islet dysfunction; decreases in GSH/PPAR-γ concentrations and increases in ROS/cysteamine might be primary cause of this effect. Clinical serum analyses revealed that the expression profiles of these molecules were aberrant in the PCAND group. Our results further demonstrated that PCAND is a type of paraneoplastic diabetes. As the only clinically derived biomarker for PCAND screening available today, the biological role of VNN1 in triggering oxidative stress within the pancreatic microenvironment is important. The molecules downstream of VNN1 are also potential biomarkers for PCAND screening.

Characterization of the role of the photosensitizer, deuteporfin, in the detection of lymphatic metastases in a pancreatic cancer xenograft model

Currently, the use of photosensitizers as tracer agents to detect lymphatic metastases is a developing area of study in the field of pancreatic cancer treatment. In the present study, deuteporfin, a novel photosensitizer, was used as a tracer agent to detect lymphatic metastases in a pancreatic cancer xenograft model. The biodistribution and pharmacokinetics of deuteporfin, following intravenous administration and injection of deuteporfin into the left rear footpad, were investigated in Sprague-Dawley rats. The increased difference in deuteporfin concentration between the cancerous and normal tissues was directly observed through the application of a Wood's lamp. In addition, the highly lymphatic BxPC-3-LN5 human metastatic pancreatic cancer cell line was generated from BxPC-3 cells using a continuous screening and seeding method in vivo. A xenograft model of the BxPC-3-LN5 human pancreatic cancer cell line transplanted into the left rear footpad of nude mice, was established. The effects of deuteporfin as a tracer agent in the detection of lymphatic metastases were then characterized in the pancreatic cancer xenograft model. Following intravenous administration, deuteporfin was rapidly enriched in the pancreas and popliteal fossa lymph nodes compared with that of the left rear footpad administration group. In addition, deuteporfin appeared to be selectively enriched in the cancerous pancreatic lymph nodes of the pancreatic cancer xenograft model. These results indicated that deuteporfin may be developed as a novel photosensitizer tracer agent for the detection of lymphatic metastases in pancreatic cancer. The advantages of deuteporfin are that it has a selective tumor-targeting effect due to high tissue uptake, and that it may be administered intravenously and is therefore suitable for surgery.

Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

Background

microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies.

Methods

In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer.

Results

Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis.

Conclusions

Our prediction models have strong potential for the diagnosis of pancreatic cancer.

Pancreatic cancer exosomes initiate pre-metastatic niche formation in the liver

Pancreatic ductal adenocarcinomas (PDACs) are highly metastatic with poor prognosis, mainly due to delayed detection. We hypothesized that intercellular communication is critical for metastatic progression. Here, we show that PDAC-derived exosomes induce liver pre-metastatic niche formation in naive mice and consequently increase liver metastatic burden. Uptake of PDAC-derived exosomes by Kupffer cells caused transforming growth factor β secretion and upregulation of fibronectin production by hepatic stellate cells. This fibrotic microenvironment enhanced recruitment of bone marrow-derived macrophages. We found that macrophage migration inhibitory factor (MIF) was highly expressed in PDAC-derived exosomes, and its blockade prevented liver pre-metastatic niche formation and metastasis. Compared with patients whose pancreatic tumours did not progress, MIF was markedly higher in exosomes from stage I PDAC patients who later developed liver metastasis. These findings suggest that exosomal MIF primes the liver for metastasis and may be a prognostic marker for the development of PDAC liver metastasis.

Recent advances in proteomically subtyping pancreatic ductal adenocarcinomas and their potential clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease with a median overall survival of 6 months. Late diagnosis due to the absence of specific symptoms during disease development, in addition to extensive metastatic potential and resistance to chemotherapy and radiotherapy, are the most important reasons for short survival. Research efforts have therefore been focused on the development of early disease detection. However, the only US FDA-approved clinical biomarker, CA19-9, is considered inapplicable for screening and/or early detection of PDAC. The following editorial provides the reader with a short introduction to the topic of PDAC and gives focus to the current state of proteomic research in the field of PDAC biomarker discovery. This editorial also highlights the efforts made to subdivide this tumor entity and the potential clinical impact of patient stratification. Finally, the author provides opinions on the impact of proteomics to PDAC subtype stratification over the next 5 years.

Validation of biomarkers that complement CA19.9 in detecting early pancreatic cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is a significant cause of cancer mortality. Carbohydrate antigen 19.9 (CA19.9), the only tumor marker available to detect and monitor PDAC, is not sufficiently sensitive and specific to consistently differentiate early cancer from benign disease. In this study, we aimed to validate recently discovered serum protein biomarkers for the early detection of PDAC and ultimately develop a biomarker panel that could discriminate PDAC from other benign disease better than the existing marker CA19.9.

PATIENTS AND METHODS

We performed a retrospective blinded evaluation of 400 serum samples collected from individuals recruited on a consecutive basis. The sample population consisted of 250 individuals with PDAC at various stages, 130 individuals with benign conditions and 20 healthy individuals. The serum levels of each biomarker were determined by ELISAs or automated immunoassay.

RESULTS

By randomly splitting matched samples into a training (n = 186) and validation (n = 214) set, we were able to develop and validate a biomarker panel consisting of CA19.9, CA125, and LAMC2 that significantly improved the performance of CA19.9 alone. Improved discrimination was observed in the validation set between all PDAC and benign conditions (AUCCA19.9 = 0.80 vs. AUCCA19.9+CA125+LAMC2 = 0.87; P < 0.005) as well as between early-stage PDAC and benign conditions (AUCCA19.9 = 0.69 vs. AUCCA19.9+CA125+LAMC2 = 0.76; P < 0.05) and between early-stage PDAC and chronic pancreatitis (CP; AUCCA19.9 = 0.59 vs. AUCCA19.9+CA125+LAMC2 = 0.74; P < 0.05).

CONCLUSIONS

The data demonstrate that a serum protein biomarker panel consisting of CA125, CA19.9, and LAMC2 is able to significantly improve upon the performance of CA19.9 alone in detecting PDAC.

Vascular endothelial growth factor receptor type 2-targeted contrast-enhanced US of pancreatic cancer neovasculature in a genetically engineered mouse model: potential for earlier detection

PURPOSE

To test ultrasonographic (US) imaging with vascular endothelial growth factor receptor type 2 (VEGFR2)-targeted microbubble contrast material for the detection of pancreatic ductal adenocarcinoma (PDAC) in a transgenic mouse model of pancreatic cancer development.

MATERIALS AND METHODS

Experiments involving animals were approved by the Institutional Administrative Panel on Laboratory Animal Care at Stanford University. Transgenic mice (n = 44; Pdx1-Cre, KRas(G12D), Ink4a(-/-)) that spontaneously develop PDAC starting at 4 weeks of age were imaged by using a dedicated small-animal US system after intravenous injection of 5 × 10(7) clinical-grade VEGFR2-targeted microbubble contrast material. The pancreata in wild-type (WT) mice (n = 64) were scanned as controls. Pancreatic tissue was analyzed ex vivo by means of histologic examination (with hematoxylin-eosin staining) and immunostaining of vascular endothelial cell marker CD31 and VEGFR2. The Wilcoxon rank sum test and linear mixed-effects model were used for statistical analysis.

RESULTS

VEGFR2-targeted US of PDAC showed significantly higher signal intensities (26.8-fold higher; mean intensity ± standard deviation, 6.7 linear arbitrary units [lau] ± 8.5; P < .001) in transgenic mice compared with normal, control pancreata of WT mice (mean intensity, 0.25 lau ± 0.25). The highest VEGFR2-targeted US signal intensities were observed in smaller tumors, less than 3 mm in diameter (30.8-fold higher than control tissue with mean intensity of 7.7 lau ± 9.3 [P < .001]; and 1.7-fold higher than lesions larger than 3 mm in diameter with mean intensity of 4.6 lau ± 5.8 [P < .024]). Ex vivo quantitative VEGFR2 immunofluorescence demonstrated that VEGFR2 expression was significantly higher in pancreatic tumors (P < .001; mean fluorescent intensity, 499.4 arbitrary units [au] ± 179.1) compared with normal pancreas (mean fluorescent intensity, 232.9 au ± 83.7).

CONCLUSION

US with clinical-grade VEGFR2-targeted microbubbles allows detection of small foci of PDAC in transgenic mice.

Serum cytokine profile in patients with pancreatic cancer

OBJECTIVE

Pancreatic ductal adenocarcinoma is a deadly disease because of late diagnosis and chemoresistance. We aimed to find a panel of serum cytokines representing diagnostic and predictive biomarkers for pancreatic cancer.

METHODS

A cytokine antibody array was performed to simultaneously identify 507 cytokines in sera of patients with pancreatic cancer and healthy controls. The nonparametric Mann-Whitney U test was used to pairwise compare the controls, the pretreated patients, and the posttreated patients. Fold changes greater than or equal to 1.5 or less than or equal to 1/1.5 were considered significant. Receiver operating characteristic curves were used to assess the performance of the model. A leave-one-out cross-validation was used for estimating prediction error.

RESULTS

Comparing the sera of pretreated patients against the control samples, the cytokines fibroblast growth factor 10 (FGF-10/keratinocyte growth factor-2 (KGF-2), chemokine (C-X-C motif) ligand 11 interferon inducible T cell alpha chemokine (I-TAC)/chemokine [C-X-C motif] ligand 11 (CXCL11), oncostatin M (OSM), osteoactivin/glycoprotein nonmetastatic melanoma protein B, and stem cell factor (SCF) were found significantly overexpressed. Besides, the cytokines CD30 ligand/tumor necrosis factor superfamily, member 8 (TNFSF8), chordin-like 2, FGF-10/KGF-2, growth/differentiation factor 15, I-TAC/CXCL11, OSM, and SCF were differentially expressed in response to treatment.

CONCLUSIONS

We propose a role for FGF-10/KGF-2, I-TAC/CXCL11, OSM, osteoactivin/glycoprotein nonmetastatic melanoma protein B, and SCF as novel diagnostic biomarkers. CD30 ligand/TNFSF8, chordin-like 2, FGF-10/KGF-2, growth/differentiation factor 15, I-TAC/CXCL11, OSM, and SCF might represent as predictive biomarkers for gemcitabine and erlotinib response of patients with pancreatic cancer.

Identification of human complement factor B as a novel biomarker candidate for pancreatic ductal adenocarcinoma

Pancreatic cancer (PC; pancreatic ductal adenocarcinoma) is characterized by significant morbidity and mortality worldwide. Although carbohydrate antigen (CA) 19-9 has been known as a PC biomarker, it is not commonly used for general screening because of its low sensitivity and specificity. Therefore, there is an urgent need to develop a new biomarker for PC diagnosis in the earlier stage of cancer. To search for a novel serologic PC biomarker, we carried out an integrated proteomic analysis for a total of 185 pooled or individual plasma from healthy donors and patients with five disease groups including chronic pancreatitis (CP), PC, and other cancers (e.g., hepatocellular carcinoma, cholangiocarcinoma, and gastric cancer) and identified complement factor b (CFB) as a candidate serologic biomarker for PC diagnosis. Immunoblot analysis of CFB revealed more than two times higher expression in plasma samples from PC patients compared with plasma from individuals without PC. Immunoprecipitation coupled to mass spectrometry analysis confirmed both molecular identity and higher expression of CFB in PC samples. CFB showed distinctly higher specificity than CA 19-9 for PC against other types of digestive cancers and in discriminating PC patients from non-PC patients (p < 0.0001). In receiver operator characteristic curve analysis, CFB showed an area under curve of 0.958 (95% CI: 0.956 to 0.959) compared with 0.833 (95% CI: 0.829 to 0.837) for CA 19-9. Furthermore, the Y-index of CFB was much higher than that of CA 19-9 (71.0 vs 50.4), suggesting that CFB outperforms CA 19-9 in discriminating PC from CP and other gastrointestinal cancers. This was further supported by immunoprecipitation and qRT-PCR assays showing higher expression of CFB in PC cell lines than in normal cell lines. A combination of CFB and CA 19-9 showed markedly improved sensitivity (90.1 vs 73.1%) over that of CFB alone in the diagnosis of PC against non-PC, with similar specificity (97.2 vs 97.9%). Thus, our results identify CFB as a novel serologic PC biomarker candidate and warrant further investigation into a large-scale validation and its role in molecular mechanism of pancreatic carcinogenesis.

Novel bispecific antibodies increase γδ T-cell cytotoxicity against pancreatic cancer cells

The ability of human γδ T cells from healthy donors to kill pancreatic ductal adenocarcinoma (PDAC) in vitro and in vivo in immunocompromised mice requires the addition of γδ T-cell-stimulating antigens. In this study, we demonstrate that γδ T cells isolated from patients with PDAC tumor infiltrates lyse pancreatic tumor cells after selective stimulation with phosphorylated antigens. We determined the absolute numbers of γδ T-cell subsets in patient whole blood and applied a real-time cell analyzer to measure their cytotoxic effector function over prolonged time periods. Because phosphorylated antigens did not optimally enhance γδ T-cell cytotoxicity, we designed bispecific antibodies that bind CD3 or Vγ9 on γδ T cells and Her2/neu (ERBB2) expressed by pancreatic tumor cells. Both antibodies enhanced γδ T-cell cytotoxicity with the Her2/Vγ9 antibody also selectively enhancing release of granzyme B and perforin. Supporting these observations, adoptive transfer of γδ T cells with the Her2/Vγ9 antibody reduced growth of pancreatic tumors grafted into SCID-Beige immunocompromised mice. Taken together, our results show how bispecific antibodies that selectively recruit γδ T cells to tumor antigens expressed by cancer cells illustrate the tractable use of endogenous γδ T cells for immunotherapy.

Biomarkers for pancreatic cancer: promising new markers and options beyond CA 19-9

Pancreatic adenocarcinoma accounts for nearly 90-95% of exocrine malignant tumors of the pancreas. Traditionally, overexpressed proteins/epitopes such as CA 19-9, CA-50, CEA, and many others were being used as pancreatic cancer tumor markers. The main utility of these biomarkers was in the diagnosis of pancreatic cancer as well as to assess response to chemotherapy and to determine prognosis and to predict tumor recurrence. However, these markers had significant limitations such as lack of sensitivity, false-negative results in certain blood groups, as well as false-positive elevation in the presence of obstructive jaundice. To circumvent these limitations, an extraordinary amount of research is being performed to identify an accurate tumor marker or a panel of markers that could aid in the management of the pancreatic cancer. Although this research has identified a large number and different variety of biomarkers, few hold future promise as a preferred marker for pancreatic cancer. This review provides an insight into exciting new areas of pancreatic biomarker research such as salivary, pancreatic juice, and stool markers that can be used as a noninvasive test to identify pancreatic cancer. This manuscript also provides a discussion on newer biomarkers, the role of microRNAs, and pancreatic cancer proteomics, which have the potential to identify a preferred tumor marker for pancreatic adenocarcinoma. This review further elaborates on important genetic changes associated with the development and progression of pancreatic cancer that holds the key for the identification of a sensitive biomarker and which could also serve as a therapeutic target.