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

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions – kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

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Urinary protein biomarkers are useful for diagnosis of many conditions: kidney and cardio vascular diseases, cancers.

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Liquid chromatography – mass spectroscopy is a powerful tool for urine proteomics, but used mostly in science.

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Immunoassays are widely used in both clinical and bio-analytical laboratories.

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IR and Raman spectroscopies are promising tools for diagnostics of urine due to low-cost and rapidness.

Volatile organic compounds (VOCs) for the non-invasive detection of pancreatic cancer from urine

Pancreatic ductal adenocarcinoma (PDAC) is a particularly challenging cancer, with very low 5-year survival rates. This low survival rate is linked to late stage diagnosis, associated with the lack of approved biomarkers. One approach that is receiving considerable attention is the use of volatile organic compounds (VOCs) that emanate from biological waste as biomarkers for disease. In this study, we used urine as our biological matrix and two VOC analysis platforms: gas chromatography - ion mobility spectrometry (GC-IMS) and GC time-of-flight mass spectrometry (GC-TOF-MS). We measured the urinary headspace of samples from patients with PDAC, chronic pancreatitis (CP) and healthy controls. In total, 123 samples were tested from these groups. Results indicate that both GC-IMS and GC-TOF-MS were able to discriminate PDAC from healthy controls with high confidence and an AUC (area under the curve) in excess of 0.85. However, both methods struggled to separate CP from PDAC, with the best result of AUC 0.58. This indicates that both conditions produce similar biomarkers in the urinary headspace. Chemical identification suggests that 2,6-dimethyl-octane, nonanal, 4-ethyl-1,2-dimethyl-benzene and 2-pentanone play an important role in separating these groups. Therefore, both techniques validate this approach in identifying subjects for further investigation in a clinical setting.

A Quantitative Global Proteomics Approach Identifies Candidate Urinary Biomarkers That Correlate With Intraductal Papillary Mucinous Neoplasm Dysplasia

OBJECTIVES

A proteomic discovery study was performed to determine if urine possesses a unique biosignature that could form the basis for a noninvasive test able to predict intraductal papillary mucinous neoplasm (IPMN) dysplasia.

METHODS

Urine was collected from patients undergoing surgery for IPMN (72 low/moderate, 27 high-grade/invasive). Quantitative mass spectrometry-based proteomics was performed. Proteins of interest were identified by differential expression analysis followed by principal component analysis.

RESULTS

Proteomics identified greater than 4800 urinary proteins. Low/moderate and high-grade/invasive IPMN were distinguished by 188 proteins (P < 0.05). Following principal component analysis and heatmap visualization, vitamin D binding protein (DBP), apolipoprotein A1 (APOA1), and alpha-1 antitrypsin (A1AT) were selected. The proteomic abundance of DBP (median [interquartile range]) was significantly higher for high-grade/invasive than for low/moderate IPMN (219,735 [128,882-269,943] vs. 112,295 [77,905-180,773] normalized reporter ion intensity units; P = 0.001). Similarly, APOA1 was more abundant in the high-grade/invasive than low/moderate groups (235,420 [144,933-371,247] vs 150,095 [103,419-236,591]; P = 0.0007) as was A1AT (567,514 [358,544-774,801] vs 358,393 [260,850-477,882]; P = 0.0006).

CONCLUSIONS

Urinary DBP, APOA1, and A1AT represent potential biomarker candidates that may provide a noninvasive means of predicting IPMN dysplastic grade.

Carboxypeptidase A1 and regenerating islet-derived 1α as new markers for pancreatic acinar cell carcinoma

Acinar cell carcinoma (ACC) is a rare tumor that differentiates toward pancreatic acinar cells and shows evidence of pancreatic enzyme production. Mixed acinar-neuroendocrine carcinoma (MANC) is defined as having more than 30% of both acinar and neuroendocrine cell types as per immunohistochemistry analysis. Trypsin is currently the most commonly used stain for acinar differentiation. In this study, we investigate the utility of two novel markers, carboxypeptidase A1 (CPA1) and regenerating islet-derived 1α (REG1a), in diagnosing ACC/MANC. Immunohistochemical staining for CPA1 and REG1a was performed on 14 cases of ACC and 5 cases of MANC as well as on 80 other pancreatic tumors including 20 cases each of ductal adenocarcinoma, well-differentiated neuroendocrine tumor, mucinous cystic neoplasm, and solid pseudopapillary tumor. All ACCs and MANCs were positive for CPA1 (all diffuse) and REG1a (12 diffuse, 4 patchy, and 3 focal). A diffuse or patchy staining pattern was significantly more common in ACC/MANC cases (100% diffuse/patchy for CPA1 and 84% for REG1a) than in other pancreatic tumors (5% diffuse/patchy for CPA1 and 7.5% for REG1a), with a P-value of <0.0001 for both CPA1 and REG1a. The sensitivity and specificity of diffuse/patchy staining for CPA1 and REG1a in diagnosing pancreatic ACC/MANC were 100% and 95% for CPA1 and 84% and 93% for REG1a, respectively. In conclusion, CPA1 and REG1a are sensitive markers for ACC that can be used as additional acinar cell differentiation markers to help in the diagnosis of pancreatic ACC and MANC. A negative result for CPA1 virtually excludes ACC/MANC.

Proteomic analysis of pancreatic ductal adenocarcinoma

INTRODUCTION

Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 80% of all pancreatic cancers, is a highly aggressive malignant disease and one of the most lethal among all cancers. Overall, the 5-year survival rate among all pancreatic cancer patients is less than 9%; these rates have shown little change over the past 30 years. A more comprehensive understanding of the molecular mechanisms underlying this complex disease is crucial to the development of new diagnostic tools for early detection and disease monitoring, as well as to identify new and more effective therapeutics to improve patient outcomes.

AREA COVERED

We summarize recent advances in proteomic strategies and mass spectrometry to identify new biomarkers for early detection and monitoring of disease progression, predict response to therapy, and to identify novel proteins that have the potential to be 'druggable' therapeutic targets. An overview of proteomic studies that have been conducted to further our mechanistic understanding of metastasis and chemotherapy resistance in PDAC disease progression will also be discussed.

EXPERT COMMENTARY

The results from these PDAC proteomic studies on a variety of PDAC sample types (e.g., blood, tissue, cell lines, exosomes, etc.) provide great promise of having a significant clinical impact and improving patient outcomes.

Proteomic Characterization of Circulating Molecular Perturbations Associated With Pancreatic Adenocarcinoma Following Intravenous ω-3 Fatty Acid and Gemcitabine Administration: A Pilot Study

BACKGROUND

Administration of intravenous ω-3 fatty acid (ω-3FA) in advanced pancreatic adenocarcinoma patients receiving gemcitabine chemotherapy shows disease stabilization and improved progression-free survival. Using high-definition plasma proteomics, the underlying biological mechanisms responsible for these clinical effects are investigated.

METHODS AND RESULTS

A pilot study involving plasma that was collected at baseline from 13 patients with histologically confirmed, unresectable pancreatic adenocarcinoma (baseline group) after 1-month treatment with intravenous gemcitabine and ω-3FA (treatment group) and intravenous gemcitabine only (control group) and was prepared for proteomic analysis. A 2-arm study comparing baseline vs treatment and treatment vs control was performed. Proteins were isolated from plasma with extensive immunodepletion, then digested and labeled with isobaric tandem mass tag peptide tags. Samples were then combined, fractionated, and injected into a QExactive-Orbitrap Mass-Spectrometer and analyzed on Proteome Discoverer and Scaffold with ensuing bioinformatics analysis. Selective reaction monitoring analysis was performed for verification. In total, 3476 proteins were identified. Anti-inflammatory markers (C-reactive protein, haptoglobin, and serum amyloid-A1) were reduced in the treatment group. Enrichment analysis showed angiogenesis downregulation, complement immune systems upregulation, and epigenetic modifications on histones. Pathway analysis identified direct action via the Pi3K-AKT pathway. Serum amyloid-A1 significantly reduced (P < .001) as a potential biomarker of efficacy for ω-3FA.

CONCLUSIONS

This pilot study demonstrates administration of ω-3FA has potential anti-inflammatory, antiangiogenic, and proapoptotic effects via direct interaction with cancer-signaling pathways in patients with advanced pancreatic adenocarcinoma. Further studies in a larger sample size is required to validate the clinical correlation found in this preliminary study.

Early detection of pancreatic cancer

Pancreatic ductal adenocarcinoma is most frequently detected at an advanced stage. Such late detection restricts treatment options and contributes to a dismal 5-year survival rate of 3-15%. Pancreatic ductal adenocarcinoma is relatively uncommon and screening of the asymptomatic adult population is not feasible or recommended with current modalities. However, screening of individuals in high-risk groups is recommended. Here, we review groups at high risk for pancreatic ductal adenocarcinoma, including individuals with inherited predisposition and patients with pancreatic cystic lesions. We discuss studies aimed at finding ways of identifying pancreatic ductal adenocarcinoma in high-risk groups, such as among individuals with new-onset diabetes mellitus and people attending primary and secondary care practices with symptoms that suggest this cancer. We review early detection biomarkers, explore the potential of using social media for detection, appraise prediction models developed using electronic health records and research data, and examine the application of artificial intelligence to medical imaging for the purposes of early detection.

Potential biomarkers for early detection of pancreatic ductal adenocarcinoma

Pancreatic cancer has the highest mortality amongst all major organ cancers. Early detection is key to reduce deaths related to pancreatic cancer. However, early detection has been challenged by the lack of non-invasive biomarkers with enough sensitivity and specificity to allow for screening. The gold standard is still carbohydrate antigen (CA 19-9), against which all new biomarkers must be evaluated. In this paper, we describe recent progress in the development of new pancreatic cancer biomarkers, focusing on proteins, metabolites, and genetic and epigenetic biomarkers. Although several promising biomarkers have been identified, they are all derived from retrospective studies and additional prospective studies are needed to confirm their clinical validity.

Application of liquid biopsy for surgical management of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest forms of cancer. Although drug development over the past decade has gradually improved the prognosis of PDAC, the prognosis remains extremely poor. The predominant determinant of a poor prognosis is that patients are already at the advanced stage when they are diagnosed. Therefore, it is essential to detect early-stage PDAC to ensure a good prognosis. However, in general, being asymptomatic at the early stage makes the detection of early-stage PDAC very difficult. Recently, much attention has been focused on the utility of a liquid biopsy as a biomarker. Theoretically, early-stage tumors can be detected even under asymptomatic conditions. A number of studies on liquid biopsies have been reported so far. Several biomarkers, including circulating tumor DNA (ctDNA), circulating tumor cells (CTCS), and exosomes, are used in liquid biopsies, with the potential to be applied to the clinical setting. Each biomarker is reported to have different utilities, such as the detection of early-stage disease, the differential diagnosis of PDAC from other types of pancreatic tumors, the prediction of the prognosis or risk of recurrence, and monitoring the treatment response. In this review, we focus on ctDNA, CTCS, and exosomes as representative liquid biopsy biomarkers and describe the specific functions of each biomarker in the treatment of PDAC. Furthermore, we discuss the application of liquid biopsies, especially for the surgical management of PDAC.

Odyssey of trefoil factors in cancer: Diagnostic and therapeutic implications

Trefoil factors 1, 2, and 3 (TFFs) are a family of small secretory molecules involved in the protection and repair of the gastrointestinal tract (GI). TFFs maintain and restore epithelial structural integrity via transducing key signaling pathways for epithelial cell migration, proliferation, and invasion. In recent years, TFFs have emerged as key players in the pathogenesis of multiple diseases, especially cancer. Initially recognized as tumor suppressors, emerging evidence demonstrates their key role in tumor progression and metastasis, extending their actions beyond protection. However, to date, a comprehensive understanding of TFFs' mechanism of action in tumor initiation, progression and metastasis remains obscure. The present review discusses the structural, functional and mechanistic implications of all three TFF family members in tumor progression and metastasis. Also, we have garnered information from studies on their structure and expression status in different organs, along with lessons from their specific knockout in mouse models. In addition, we highlight the emerging potential of using TFFs as a biomarker to stratify tumors for better therapeutic intervention.

Update on urine as a biomarker in cancer: a necessary review of an old story

Introduction: Cancer causes thousands of deaths worldwide each year. Therefore, monitoring of health status and the early diagnosis of cancer using noninvasive assays, such as the analysis of molecular biomarkers in urine, is essential. However, effective biomarkers for early diagnosis of cancer have not been established in many types of cancer.Areas covered: In this review, we discuss recent findings with regard to the use of urine composition as a biomarker in eleven types of cancer. We also highlight the use of urine biomarkers for improving early diagnosis.Expert opinion: Urinary biomarkers have been applied for clinical application of early diagnosis. The main limitation is a lack of integrated approaches for identification of new biomarkers in most cancer. The utilization of urinary biomarker detection will be promoted by improved detection methods and new data from different types of cancers. With the development of precision medicine, urinary biomarkers will play an increasingly important clinical role. Future early diagnosis would benefit from changes in the utilization of urinary biomarkers.

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

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

A comprehensive analysis of candidate genes in familial pancreatic cancer families reveals a high frequency of potentially pathogenic germline variants

BACKGROUND

The 5-year survival rate of patients with pancreatic ductal adenocarcinoma (PDAC) is around 5% due to the fact that the majority of patients present with advanced disease that is treatment resistant. Familial pancreatic cancer (FPC) is a rare disorder that is defined as a family with at least two affected first degree relatives, with an estimated incidence of 4%-10%. The genetic basis is unknown in the majority of families although around 10%-13% of families carry germline mutations in known genes associated with hereditary cancer and pancreatitis syndromes.

METHODS

Panel sequencing was performed of 35 genes associated with hereditary cancer in 43 PDAC cases from families with an apparent hereditary pancreatic cancer syndrome.

FINDINGS

Pathogenic variants were identified in 19% (5/26) of PDAC cases from pure FPC families in the genes MLH1, CDKN2A, POLQ and FANCM. Low frequency potentially pathogenic VUS were also identified in 35% (9/26) of PDAC cases from FPC families in the genes FANCC, MLH1, PMS2, CFTR, APC and MUTYH. Furthermore, an important proportion of PDAC cases harboured more than one pathogenic, likely pathogenic or potentially pathogenic VUS, highlighting the multigene phenotype of FPC.

INTERPRETATION

The genetic basis of familial or hereditary pancreatic cancer can be explained in 21% of families by previously described hereditary cancer genes. Low frequency variants in other DNA repair genes are also present in 35% of families which may contribute to the risk of pancreatic cancer development.

FUNDING

This study was funded by the Instituto de Salud Carlos III (Plan Estatal de I + D + i 2013-2016): ISCIII (PI09/02221, PI12/01635, PI15/02101 and PI18/1034) and co-financed by the European Development Regional Fund ''A way to achieve Europe'' (ERDF), the Biomedical Research Network in Cancer: CIBERONC (CB16/12/00446), Red Temática de investigación cooperativa en cáncer: RTICC (RD12/0036/0073) and La Asociación Española contra el Cáncer: AECC (Grupos Coordinados Estables 2016).

Detection of pancreatic ductal adenocarcinoma with galectin-9 serum levels

Pancreatic ductal adenocarcinoma (PDAC) responds poorly to checkpoint blockade, such as anti-CTLA-4 and anti-PD-1. Galectin-9, a β-galactoside-binding lectin, promotes immune suppression through T-cell inhibition, and programming of tolerogenic macrophages. Of all cancers tested, PDAC showed the highest expression of LGALS9 (galectin-9) mRNA. We analyzed formalin-fixed and paraffin-embedded specimens from 83 patients with PDAC stained for galectin-9. Using flow cytometry, we determined galectin-9 expression on immune cells from tumor and matched blood samples from 12 patients with resectable PDAC. Furthermore, we analyzed galectin-9 serum levels by enzyme-linked immunosorbent assay using serum samples from 70 patients with PDAC, from 36 individuals with benign pancreatic disease, and from 28 healthy controls. Galectin-9 was highly expressed in human PDAC compared with normal pancreas and present on both tumor and immune cells. Tumor-infiltrating immune cells, especially CD3⁺ T cells, showed upregulation of galectin-9 compared with immune cells from matched blood. Blood γδ T cells from PDAC patients had higher galectin-9 expression than γδ T cells from healthy individuals. Galectin-9 polarized macrophages toward a protumoral M2 phenotype leading to suppressed T-cell cytokine secretion. Furthermore, serum concentration of galectin-9 was able to discriminate PDAC from benign pancreatic disease and healthy individuals, and was prognostic for stage IV patients. Galectin-9 is a new biomarker for the detection of PDAC.

Urine α-fetoprotein and orosomucoid 1 as biomarkers of hepatitis B virus-associated hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the sixth common malignant tumor worldwide, but current efficient and convenient screening methods remain lacking. This study aimed to discover a diagnostic or a screening biomarker from the urine of hepatitis B virus (HBV)-related HCC patients. We used iTRAQ coupled with mass spectrometry to identify candidate urinary proteins in a discovery cohort (n = 40). The selected proteins were confirmed using ELISA in a validation cohort (n = 140). Diagnostic performance of the selected proteins was assessed using receiver operating characteristic (ROC) and qualitative diagnostic analysis. A total of 96 differentially expressed proteins were identified. Urinary α-fetoprotein (u-AFP) and orosomucoid 1 (u-ORM1) were selected as target proteins by bioinformatics analysis and were significantly higher in HCC than in non-HCC patients, as validated by Western blot analysis and ELISA. u-AFP had a strong correlation with serum AFP-L3 (Pearson's r = 0.944, P < 0.0001), indicating that u-AFP may be derived from circulating blood. The area under the curve (AUC) of u-AFP was 0.795 with a sensitivity of 62.5% and a specificity of 95.4%, which showed no significantly difference with serum AFP (se-AFP). The AUC was 0.864 as u-AFP and u-ORM1 were combined, and they performed much better than u-AFP or u-ORM1 alone. Qualitative diagnostic analysis showed that the positive predictive value of u-AFP was 90.1% and the diagnostic sensitivity of parallel combination of u-AFP and u-ORM1 was 85.1%. Taken together, AFP and ORM1 in the urine may be used as a diagnostic or screening biomarker of HCC, and studies on large samples are needed to validate the result.NEW & NOTEWORTHY This study provides a novel way to find biomarkers of hepatocellular carcinoma (HCC) and a new perspective of α-fetoprotein clinical application. The urine reagent strips may be helpful in high epidemic areas of HCC and in low-resource settings.

Familial Pancreatic Cancer: Current Perspectives

Pancreatic cancer (PC) is a highly lethal disease, mostly incurable when detected. Thus, despite advances in PC treatments, only around 7% of patients survive 5-years after diagnosis. This morbid outcome is secondary to multifactorial reasons, such as late-stage diagnosis, rapid progression and minimal response to chemotherapy. Based on these factors, it is of special relevance to identify PC high-risk individuals in order to establish preventive and early detection measures. Although most PC are sporadic, approximately 10% cases have a familial basis. No main causative gene of PC has been identified but several known germline pathogenic mutations are related with an increased risk of this tumor. These inherited cancer syndromes represent 3% of all PC. On the other hand, in 7% of cases of PC, there is a strong family history without a causative germline mutation, a situation known as familial pancreatic cancer (FPC). In recent years, there is increasing evidence supporting the benefit of genetic germline analysis in PC patients, and periodic pancreatic screening in PC high-risk patients (mainly those with a lifetime risk greater than 5%), although there is no general agreement in the group of patients and individuals to study and screen. In the present review, we expose an update in the field of hereditary and FPC, with the aim of describing the current strategies and implications in genetic counseling, surveillance and therapeutic interventions.

Cancer metabolomic markers in urine: evidence, techniques and recommendations

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

Combined detection of CA19-9 and B7-H4 in the diagnosis and prognosis of pancreatic cancer

BACKGROUND

There were no specific indicators for the early detection of pancreatic cancer.

OBJECTIVE

To analyze the diagnostic and prognostic value of CA19-9 plus B7-H4 detection in preoperative serum or surgical tissues of patients with pancreatic cancer.

METHODS

One hundred and eighty-eight patients with pancreatic cancer and 25 controls were recruited. Their preoperative serum CA19-9 level was detected chemiluminescently, and B7-H4 expression in pancreatic cancer tissues was assessed immunohistochemically. The diagnostic and prognostic utility of detecting CA19-9, B7-H4 and their combination was evaluated.

RESULTS

CA19-9 and B7-H4 levels were significantly upregulated in patients with pancreatic cancer compared with those in controls. The diagnostic value of combined CA19-9 plus B7-H4 detection was markedly better than that achieved from their separate detection analyzed with receiver operating characteristic curve. Sensitivity and specificity of the combined detection in the pancreatic cancer group was significantly increased compared with single detection. B7-H4 detection showed better prognostic value than detection of CA19-9. However, CA19-9 had high sensitivity and low specificity, while B7-H4 showed the opposite. The sensitivity of the combined prognosis was not significantly different to B7-H4 alone.

CONCLUSION

The combined detection of CA19-9 and B7-H4 could become a new method for the clinical diagnosis and prognosis of pancreatic cancer.

Urine metallomics signature as an indicator of pancreatic cancer

Urine metallomics as potential diagnostic tool for PDAC, one of the deadliest types of cancer.

Development of PancRISK, a urine biomarker-based risk score for stratified screening of pancreatic cancer patients

Background

An accurate and simple risk prediction model that would facilitate earlier detection of pancreatic adenocarcinoma (PDAC) is not available at present. In this study, we compare different algorithms of risk prediction in order to select the best one for constructing a biomarker-based risk score, PancRISK.

Methods

Three hundred and seventy-nine patients with available measurements of three urine biomarkers, (LYVE1, REG1B and TFF1) using retrospectively collected samples, as well as creatinine and age, were randomly split into training and validation sets, following stratification into cases (PDAC) and controls (healthy patients). Several machine learning algorithms were used, and their performance characteristics were compared. The latter included AUC (area under ROC curve) and sensitivity at clinically relevant specificity.

Results

None of the algorithms significantly outperformed all others. A logistic regression model, the easiest to interpret, was incorporated into a PancRISK score and subsequently evaluated on the whole data set. The PancRISK performance could be even further improved when CA19-9, commonly used PDAC biomarker, is added to the model.

Conclusion

PancRISK score enables easy interpretation of the biomarker panel data and is currently being tested to confirm that it can be used for stratification of patients at risk of developing pancreatic cancer completely non-invasively, using urine samples.

Clinical significance of urinary plasminogen and fibrinogen gamma chain as novel potential diagnostic markers for non-small-cell lung cancer

BACKGROUND

Urinary proteins could be useful as markers for the detection of non-small-cell lung cancer (NSCLC). We investigated the levels of two different proteins in urine samples from NSCLC patients and assessed their diagnostic value.

METHODS

Urinary plasminogen (PLG) and fibrinogen gamma chain (FGG) levels in 112 NSCLC patients and 197 controls were detected using enzyme linked immunosorbent assay (ELISA). The expression of FGG and PLG in 20 NSCLC tissues and paired adjacent non-tumour tissues were detected through immunohistochemistry. The diagnostic value of FGG and PLG for NSCLC was evaluated through a receiver operating characteristic curve (ROC).

RESULTS

PLG and FGG were significantly elevated in NSCLC tissues vs paired adjacent non-tumour tissues (p = 0.000) and in urinary samples from NSCLC patients vs healthy controls (p = 0.000). The expression level of PLG in urinary samples was related only to the histological type (p = 0.001). Further, ROC curve analysis revealed that PLG, FGG, and their combination could distinguish NSCLC and its subtypes from healthy controls with an AUC ranging from 0.827 to 0. 947. By comparing urine samples with matching plasma CEA from NSCLC stage I-IV patients (n = 81) and healthy controls (n = 31), the combination of CEA with PLG or FGG showed that the AUC was 0.889 and 0.806, respectively, which is superior to a single biomarker alone.

CONCLUSIONS

These two urinary proteins could serve as potential markers for the diagnosis of NSCLC.

A Virus-Infected, Reprogrammed Somatic Cell-Derived Tumor Cell (VIReST) Vaccination Regime Can Prevent Initiation and Progression of Pancreatic Cancer

PURPOSE

Pancreatic cancer remains one of the most lethal cancers, and late detection renders most tumors refractory to conventional therapies. Development of cancer prophylaxis may be the most realistic option for improving mortality associated with this disease. Here, we develop a novel individualized prophylactic and therapeutic vaccination regimen using induced pluripotent stem cells (iPSC), gene editing, and tumor-targeted replicating oncolytic viruses.

EXPERIMENTAL DESIGN

We created a Virus-Infected, Reprogrammed Somatic cell-derived Tumor cell (VIReST) regime. iPSCs from healthy cells were induced to pancreatic tumor cells using in situ gene editing via stable provision of KRas ^G12D and p53 ^R172H tumor driver mutations. These cells were preinfected with oncolytic Adenovirus (AdV) as prime or Vaccinia virus (VV) as boost, to improve vaccine immunogenicity, prior to delivery of vaccines in a sequential regime to young KPC transgenic mice, genetically programmed to develop pancreatic cancer, to prevent and delay disease development.

RESULTS

Tumor cells preinfected with oncolytic AdV as prime or VV as boost were the best regime to induce tumor-specific immunity. iPSC-derived tumor cells were highly related in antigen repertoire to pancreatic cancer cells of KPC transgenic mice, suggesting that an individual's stem cells can provide an antigenically matched whole tumor cell vaccine. The VIReST vaccination primed tumor-specific T-cell responses, resulting in delayed disease emergence and progression and significantly prolonged survival of KPC transgenic mice. Importantly, this regime was well-tolerated and nontoxic.

CONCLUSIONS

These results provide both proof of concept and a robust technology platform for the development of personalized prophylactic cancer vaccines to prevent pancreatic malignancies in at-risk individuals.

Fecal microbiome signatures of pancreatic cancer patients

Pancreatic cancer (PC) is a leading cause of cancer-related death in developed countries, and since most patients have incurable disease at the time of diagnosis, developing a screening method for early detection is of high priority. Due to its metabolic importance, alterations in pancreatic functions may affect the composition of the gut microbiota, potentially yielding biomarkers for PC. However, the usefulness of these biomarkers may be limited if they are specific for advanced stages of disease, which may involve comorbidities such as biliary obstruction or diabetes. In this study we analyzed the fecal microbiota of 30 patients with pancreatic adenocarcinoma, 6 patients with pre-cancerous lesions, 13 healthy subjects and 16 with non-alcoholic fatty liver disease, using amplicon sequencing of the bacterial 16S rRNA gene. Fourteen bacterial features discriminated between PC and controls, and several were shared with findings from a recent Chinese cohort. A Random Forest model based on the microbiota classified PC and control samples with an AUC of 82.5%. However, inter-subject variability was high, and only a small part of the PC-associated microbial signals were also observed in patients with pre-cancerous pancreatic lesions, implying that microbiome-based early detection of such lesions will be challenging.

Four Decades After the Discovery of Regenerating Islet-Derived (Reg) Proteins: Current Understanding and Challenges

Regenerating islet-derived (Reg) proteins have emerged as multifunctional agents with pro-proliferative, anti-apoptotic, differentiation-inducing and bactericidal properties. Over the last 40 years since first discovered, Reg proteins have been implicated in a gamut of maladies including diabetes, various types of cancer of the digestive tract, and Alzheimer disease. Surprisingly though, a consensus is still absent on the regulation of their expression, and molecular underpinning of their function. Here, we provide a critical appraisal of recent findings in the field of Reg protein biology. Specifically, the structural characteristics are reviewed particularly in connection with established or purported functions of different members of the Reg family. Moreover, Reg expression patterns in different tissues both under normal and pathophysiological conditions are summarized. Putative receptors and cascades reported to relay Reg signaling inciting cellular responses are presented aiming at a better appreciation of the biological activities of the distinct Reg moieties. Challenges are also discussed that have hampered thus far the rapid progress in this field such as the use of non-standard nomenclature for Reg molecules among various research groups, the existence of multiple Reg members with significant degree of homology and possibly compensatory modes of action, and the need for common assays with robust readouts of Reg activity. Coordinated research is warranted going forward, given that several research groups have independently linked Reg proteins to diseased states and raised the possibility that these biomolecules can serve as therapeutic targets and biomarkers.

Performance of candidate urinary biomarkers for pancreatic cancer - Correlation with pancreatic cyst malignant progression?

BACKGROUND

Intraductal papillary mucinous neoplasms (IPMN) are precursors of pancreatic cancer. Potential biomarkers of IPMN progression have not been identified in urine. A few urinary biomarkers were reported to be predictive of pancreatic ductal adenocarcinoma (PDAC). Here, we seek to assess their ability to detect high-risk IPMN.

METHODS

Urine was collected from patients undergoing pancreatic resection and healthy controls. TIMP-1(Tissue Inhibitor of Metalloproteinase-1), LYVE-1(Lymphatic Vessel Endothelial Receptor 1), and PGEM(Prostaglandin E Metabolite) levels were determined by ELISA and analyzed by Kruskal-Wallis.

RESULTS

Median urinary TIMP-1 levels were significantly lower in healthy controls (n = 9; 0.32 ng/mg creatinine) compared to PDAC (n = 13; 1.95) but not significantly different between low/moderate-grade (n = 20; 0.71) and high-grade/invasive IPMN (n = 20; 1.12). No significant difference in urinary LYVE-1 was detected between IPMN low/moderate (n = 16; 0.37 ng/mg creatinine) and high/invasive grades (n = 21; 0.09). Urinary PGEM levels were not significantly different between groups.

CONCLUSIONS

Urinary TIMP-1, LYVE-1, and PGEM do not correlate with malignant potential of pancreatic cysts.

Review and Comparison of Cancer Biomarker Trends in Urine as a Basis for New Diagnostic Pathways

Cancer is one of the major causes of mortality worldwide and its already large burden is projected to increase significantly in the near future with a predicted 22 million new cancer cases and 13 million cancer-related deaths occurring annually by 2030. Unfortunately, current procedures for diagnosis are characterized by low diagnostic accuracies. Given the proved correlation between cancer presence and alterations of biological fluid composition, many researchers suggested their characterization to improve cancer detection at early stages. This paper reviews the information that can be found in the scientific literature, regarding the correlation of different cancer forms with the presence of specific metabolites in human urine, in a schematic and easily interpretable form, because of the huge amount of relevant literature. The originality of this paper relies on the attempt to point out the odor properties of such metabolites, and thus to highlight the correlation between urine odor alterations and cancer presence, which is proven by recent literature suggesting the analysis of urine odor for diagnostic purposes. This investigation aims to evaluate the possibility to compare the results of studies based on different approaches to be able in the future to identify those compounds responsible for urine odor alteration.

A robust 6-mRNA signature for prognosis prediction of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. PDAC prognostic and diagnostic biomarkers are still being explored. The aim of this study is to establish a robust molecular signature that can improve the ability to predict PDAC prognosis. 155 overlapping differentially expressed genes between tumor and non-tumor tissues from three Gene Expression Omnibus (GEO) datasets were explored. A least absolute shrinkage and selection operator method (LASSO) Cox regression model was employed for selecting prognostic genes. We developed a 6-mRNA signature that can distinguish high PDAC risk patients from low risk patients with significant differences in overall survival (OS). We further validated this signature prognostic value in three independent cohorts (GEO batch, P < 0.0001; ICGC, P = 0.0036; Fudan, P = 0.029). Furthermore, we found that our signature remained significant in patients with different histologic grade, TNM stage, locations of tumor entity, age and gender. Multivariate cox regression analysis showed that 6-mRNA signature can be an independent prognostic marker in each of the cohorts. Receiver operating characteristic curve (ROC) analysis also showed that our signature possessed a better predictive role of PDAC prognosis. Moreover, the gene set enrichment analysis (GSEA) analysis showed that several tumorigenesis and metastasis related pathways were indeed associated with higher scores of risk. In conclusion, identifying the 6-mRNA signature could provide a valuable classification method to evaluate clinical prognosis and facilitate personalized treatment for PDAC patients. New therapeutic targets may be developed upon the functional analysis of the classifier genes and their related pathways.

Omics Approaches in Pancreatic Adenocarcinoma

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

MicroRNA-7 directly targets Reg1 in pancreatic cells

Regenerating islet-derived (Reg) proteins, which were first discovered in the pancreas, are associated with increased proliferation, prevention of apoptosis, and enhanced differentiation in normal and disease states, but very little is known about the regulation of their expression. We hypothesized that Reg expression is influenced by microRNAs. Bioinformatic analysis predicted Reg1 to be a target of microRNA-7 (miR-7), which influences pancreatic β-cell function. To this end, we investigated the effects of miR-7 on Reg1 expression in pancreatic acinar and islet β-cells. High levels of Reg1 were noted by immunostaining and Western blotting in acinar cells in contrast to islet cells. A reciprocal expression pattern was observed for miR-7. Overexpression of miR-7 resulted in Reg1 mRNA suppression and reduction of secreted Reg1 protein. Conversely, miR-7 knockdown led to increases in Reg1. Targeting of Reg1 by miR-7 was confirmed via luciferase activity assays. In contrast, miR-7 did not directly repress the human ortholog of Reg1 REG1A as well as REG1B indicating species differences in the regulation of Reg expression. This is the first account of microRNA modulation of any Reg member warranting studies to fill gaps in our knowledge of Reg protein biology, particularly in disease contexts.

A Panel of Three Biomarkers Identified by iTRAQ for the Early Diagnosis of Pancreatic Cancer

PURPOSE

Due to a lack of early diagnostic markers, pancreatic cancer (PC) remains a lethal disease. Proteomic approaches are now being applied to identify novel PC biomarkers.

EXPERIMENTAL DESIGN

In this study, iTRAQ and LC-MS/MS are used to perform comparative analyses of serum from PC patients and healthy controls (HC), to identify specific serum biomarkers for PC. Serum levels of candidate proteins are determined using ELISA.

RESULTS

Among 869 proteins identified, 55 are potential biomarkers; Vitamin K-dependent protein Z (PROZ) and tumor necrosis factor receptor superfamily member 6b (TNFRSF6B) are selected for further analysis. Serum levels of PROZ and TNFRSF6B are significantly higher in PC patients than in HC or pancreatic benign controls (BC) (p < 0.01). The AUCs range from 0.816 to 0.971 for PROZ, TNFRSF6B, and carbohydrate antigen 19-9, either individually or in combination, in PC versus HC+BC, and from 0.711 to 0.932 in PC Stage I versus HC+BC.

CONCLUSIONS AND CLINICAL RELEVANCE

It is demonstrated that PROZ and TNFRSF6B are novel serum biomarkers for detecting early stage PC, and for distinguishing PC from pancreatic benign tumor and healthy individuals. Additional large cohort studies are needed to develop PROZ and TNFRSF6B as clinical PC biomarkers.

Trefoil factor(s) and CA19.9: A promising panel for early detection of pancreatic cancer

Background

Trefoil factors (TFF1, TFF2, and TFF3) are small secretory molecules that recently have gained significant attention in multiple studies as an integral component of pancreatic cancer (PC) subtype-specific gene signature. Here, we comprehensively investigated the diagnostic potential of all the member of trefoil family, i.e., TFF1, TFF2, and TFF3 in combination with CA19.9 for detection of PC.

Methods

Trefoil factors (TFFs) gene expression was analyzed in publicly available cancer genome datasets, followed by assessment of their expression in genetically engineered spontaneous mouse model (GEM) of PC (KrasG12D; Pdx1-Cre (KC)) and in human tissue microarray consisting of normal pancreas adjacent to tumor (NAT), precursor lesions (PanIN), and various pathological grades of PC by immunohistochemistry (IHC). Serum TFFs and CA19.9 levels were evaluated via ELISA in comprehensive sample set (n = 362) comprised of independent training and validation sets each containing benign controls (BC), chronic pancreatitis (CP), and various stages of PC. Univariate and multivariate logistic regression and receiver operating characteristic curves (ROC) were used to examine their diagnostic potential both alone and in combination with CA19.9.

Findings

The publicly available datasets and expression analysis revealed significant increased expression of TFF1, TFF2, and TFF3 in human PanINs and PC tissues. Assessment of KC mouse model also suggested upregulated expression of TFFs in PanIN lesions and early stage of PC. In serum analyses studies, TFF1 and TFF2 were significantly elevated in early stages of PC in comparison to benign and CP control group while significant elevation in TFF3 levels were observed in CP group with no further elevation in its level in early stage PC group. In receiver operating curve (ROC) analyses, combination of TFFs with CA19.9 emerged as promising panel for discriminating early stage of PC (EPC) from BC (AUC_{TFF1+TFF2+TFF3+CA19.9} = 0.93) as well as CP (AUC_{TFF1+TFF2+TFF3+CA19.9} = 0.93). Notably, at 90% specificity (desired for blood-based biomarker panel), TFFs combination improved CA19.9 sensitivity by 10% and 25% to differentiate EPC from BC and CP respectively. In an independent blinded validation set, the combination of TFFs and CA19.9 (AUC_{TFF1+TFF2+TFF3+CA19.9} = 0.82) also improved the overall efficacy of CA19.9 (AUC_CA19.9 = 0.66) to differentiate EPC from CP proving unique biomarker capabilities of TFFs to distinguish early stage of this deadly lethal disease.

Interpretation

In silico, tissue and serum analyses validated significantly increased level of all TFFs in precursor lesions and early stages of PC. The combination of TFFs enhanced sensitivity and specificity of CA19.9 to discriminate early stage of PC from benign control and chronic pancreatitis groups.

Proteomics biomarkers for solid tumors: Current status and future prospects

Cancer is a heterogeneous multifactorial disease, which continues to be one of the main causes of death worldwide. Despite the extensive efforts for establishing accurate diagnostic assays and efficient therapeutic schemes, disease prevalence is on the rise, in part, however, also due to improved early detection. For years, studies were focused on genomics and transcriptomics, aiming at the discovery of new tests with diagnostic or prognostic potential. However, cancer phenotypic characteristics seem most likely to be a direct reflection of changes in protein metabolism and function, which are also the targets of most drugs. Investigations at the protein level are therefore advantageous particularly in the case of in-depth characterization of tumor progression and invasiveness. Innovative high-throughput proteomic technologies are available to accurately evaluate cancer formation and progression and to investigate the functional role of key proteins in cancer. Employing these new highly sensitive proteomic technologies, cancer biomarkers may be detectable that contribute to diagnosis and guide curative treatment when still possible. In this review, the recent advances in proteomic biomarker research in cancer are outlined, with special emphasis placed on the identification of diagnostic and prognostic biomarkers for solid tumors. In view of the increasing number of screening programs and clinical trials investigating new treatment options, we discuss the molecular connections of the biomarkers as well as their potential as clinically useful tools for diagnosis, risk stratification and therapy monitoring of solid tumors.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Liquid biopsies for management of pancreatic cancer

Pancreatic cancer is one of the main causes of cancer-related deaths worldwide. It is asymptomatic at an early stage, and most diagnosis occurs when the disease is already at a late stage, by which time the tumor is nonresectable. In order to increase the overall survival of patients with pancreatic cancer, as well as to decrease the cancer burden, it is necessary to perform early diagnosis, prognosis stratifications and cancer monitoring using accurate, minimally invasive, and cost-effective methods. Liquid biopsies seek to detect tumor-associated biomarkers in a variety of extractable body fluids and can help to monitor treatment response and disease progression, and even predict patient outcome. In patients with pancreatic cancer, tumor-derived materials, primarily circulating tumor DNA, circulating tumor cells and exosomes, are being studied for inclusion in the management of the disease. This review focuses on describing the biology of these biomarkers, methods for their enrichment and detection, as well as their potential for clinical application. Moreover, we discuss the future direction of liquid biopsies and introduce how they can be exploited toward point of care personalized medicine for the management of pancreatic cancer.

Serum Biomarker Signature-Based Liquid Biopsy for Diagnosis of Early-Stage Pancreatic Cancer

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival of < 10% because of diffuse symptoms leading to late-stage diagnosis. That survival could increase significantly if localized tumors could be detected early. Therefore, we used multiparametric analysis of blood samples to obtain a novel biomarker signature of early-stage PDAC. The signature was derived from a large patient cohort, including patients with well-defined early-stage (I and II) PDAC. This biomarker signature was validated subsequently in an independent patient cohort.

PATIENTS AND METHODS

The biomarker signature was derived from a case-control study, using a Scandinavian cohort, consisting of 16 patients with stage I, 132 patients with stage II, 65 patients with stage III, and 230 patients with stage IV PDAC, and 888 controls. This signature was validated subsequently in an independent case-control cohort in the United States with 15 patients with stage I, 75 patients with stage II, 15 patients with stage III, and 38 patients with stage IV PDAC, and 219 controls. An antibody microarray platform was used to identify the serum biomarker signature associated with early-stage PDAC.

RESULTS

Using the Scandinavian case-control study, a biomarker signature was created, discriminating samples derived from patients with stage I and II from those from controls with a receiver operating characteristic area under the curve value of 0.96. This signature, consisting of 29 biomarkers, was then validated in an independent case-control study in the United States. The biomarker signature could discriminate patients with stage I and II PDAC from controls in this independent patient cohort with a receiver operating characteristic area under the curve value of 0.96.

CONCLUSION

This serum biomarker signature might represent a tenable approach to detecting early-stage, localized PDAC if these findings are supported by a prospective validation study.

The Use of Biomarkers in Early Diagnostics of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal solid malignancies with increasing incidence. The poor prognosis is due to the aggressive nature of the tumor, late detection, and the resistance to chemotherapy and radiotherapy. A radical surgery procedure is the only treatment that has been shown to improve the 5-year survival rate to 20-25%. However, the majority of patients (80-85%) are diagnosed with locally advanced or metastatic disease and just 15-20% patients are diagnosed in an early stage allowing them to undergo the potentially curative surgical resection. The early detection of PDAC without the use of invasive methods is challenging and discovery of a cost-effective biomarker with high specificity and sensitivity could significantly improve the treatment and survival in these patients. In this review, we summarize current and newly examined biomarkers in early PDAC detection.

Glycoprotein biomarkers for the detection of pancreatic ductal adenocarcinoma

Pancreatic cancer (PaC) shows a clear tendency to increase in the next years and therefore represents an important health and social challenge. Currently, there is an important need to find biomarkers for PaC early detection because the existing ones are not useful for that purpose. Recent studies have indicated that there is a large window of time for PaC early detection, which opens the possibility to find early biomarkers that could greatly improve the dismal prognosis of this tumor. The present manuscript reviews the state of the art of the existing PaC biomarkers. It focuses on the anomalous glycosylation process and its role in PaC. Glycan structures of glycoconjugates such as glycoproteins are modified in tumors and these modifications can be detected in biological fluids of the cancer patients. Several studies have found serum glycoproteins with altered glycan chains in PaC patients, but they have not shown enough specificity for PaC. To find more specific cancer glycoproteins we propose to analyze the glycan moieties of a battery of glycoproteins that have been reported to increase in PaC tissues and that can also be found in serum. The combination of these new candidate glycoproteins with their aberrant glycosylation together with the existing biomarkers could result in a panel, which would expect to give better results as a new tool for early diagnosis of PaC and to monitor the disease.

Quantitative proteomic analysis of pancreatic cyst fluid proteins associated with malignancy in intraductal papillary mucinous neoplasms

Background

The application of advanced imaging technologies for identifying pancreatic cysts has become widespread. However, accurately differentiating between low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive intraductal papillary mucinous neoplasms (IPMNs) remains a diagnostic challenge with current biomarkers, necessitating the development of novel biomarkers that can distinguish IPMN malignancy.

Methods

Cyst fluid samples were collected from nine IPMN patients (3 LGD, 3 HGD, and 3 invasive IPMN) during their pancreatectomies. An integrated proteomics approach that combines filter-aided sample preparation, stage tip-based high-pH fractionation, and high-resolution MS was applied to acquire in-depth proteomic data of pancreatic cyst fluid and discover marker candidates for IPMN malignancy. Biological processes of differentially expressed proteins that are related to pancreatic cysts and aggressive malignancy were analyzed using bioinformatics tools such as gene ontology analysis and Ingenuity pathway analysis. In order to confirm the validity of the marker candidates, 19 cyst fluid samples were analyzed by western blot.

Results

A dataset of 2992 proteins was constructed from pancreatic cyst fluid samples. A subsequent analysis found 2963 identified proteins in individual samples, 2837 of which were quantifiable. Differentially expressed proteins between histological grades of IPMN were associated with pancreatic diseases and malignancy according to ingenuity pathway analysis. Eighteen biomarker candidates that were differentially expressed across IPMN histological grades were discovered—7 DEPs that were upregulated and 11 that were downregulated in more malignant grades. HOOK1 and PTPN6 were validated by western blot in an independent cohort, the results of which were consistent with our proteomic data.

Conclusions

This study demonstrates that novel biomarker candidates for IPMN malignancy can be discovered through proteomic analysis of pancreatic cyst fluid.

Electronic supplementary material

The online version of this article (10.1186/s12014-018-9193-1) contains supplementary material, which is available to authorized users.

Identification of urine biomarkers associated with lung adenocarcinoma

Lung adenocarcinoma (LAC) progression is accompanied by changes in protein levels that may be reflected in body fluids, such as urine. Urine collected from LAC patients (n=34) and healthy controls (n=36) was analyzed via matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. The results revealed 76 urinary polypeptides significantly different between LAC patients and normal controls (P<0.05). Twenty-two of these peptides were up-regulated and 54 were down-regulated. Thirteen peptides had average peak intensities >600. Twelve of these 13 peptides were successfully identified using nano-liquid chromatography-tandem MS. Receiver operating characteristic analyses identified seven peptides with superior LAC diagnostic performances. Immunohistochemical staining in 20 paired LAC and adjacent normal tissues showed that IGKC, AAT, SH3BGRL3, osteopontin and gelsolin levels were higher in LAC tissues than in adjacent tissuesand were closely associated with LAC. Urinary peptides assessments may thus provide a novel, noninvasive, repeatable method for detecting and monitoring LAC. New, low-cost detection methods and bioinformatics tools are therefore urgently needed for the analysis of low abundance proteins and peptides in body fluids.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.

Detection of early pancreatic ductal adenocarcinoma with thrombospondin-2 and CA19-9 blood markers

Markers are needed to facilitate early detection of pancreatic ductal adenocarcinoma (PDAC), which is often diagnosed too late for effective therapy. Starting with a PDAC cell reprogramming model that recapitulated the progression of human PDAC, we identified secreted proteins and tested a subset as potential markers of PDAC. We optimized an enzyme-linked immunosorbent assay (ELISA) using plasma samples from patients with various stages of PDAC, from individuals with benign pancreatic disease, and from healthy controls. A phase 1 discovery study (n = 20), a phase 2a validation study (n = 189), and a second phase 2b validation study (n = 537) revealed that concentrations of plasma thrombospondin-2 (THBS2) discriminated among all stages of PDAC consistently. The receiver operating characteristic (ROC) c-statistic was 0.76 in the phase 1 study, 0.84 in the phase 2a study, and 0.87 in the phase 2b study. The plasma concentration of THBS2 was able to discriminate resectable stage I cancer as readily as stage III/IV PDAC tumors. THBS2 plasma concentrations combined with those for CA19-9, a previously identified PDAC marker, yielded a c-statistic of 0.96 in the phase 2a study and 0.97 in the phase 2b study. THBS2 data improved the ability of CA19-9 to distinguish PDAC from pancreatitis. With a specificity of 98%, the combination of THBS2 and CA19-9 yielded a sensitivity of 87% for PDAC in the phase 2b study. A THBS2 and CA19-9 blood marker panel measured with a conventional ELISA may improve the detection of patients at high risk for PDAC.

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.

Urine Proteome Profiling Predicts Lung Cancer from Control Cases and Other Tumors

Development of noninvasive, reliable biomarkers for lung cancer diagnosis has many clinical benefits knowing that most of lung cancer patients are diagnosed at the late stage. For this purpose, we conducted proteomic analyses of 231 human urine samples in healthy individuals (n = 33), benign pulmonary diseases (n = 40), lung cancer (n = 33), bladder cancer (n = 17), cervical cancer (n = 25), colorectal cancer (n = 22), esophageal cancer (n = 14), and gastric cancer (n = 47) patients collected from multiple medical centers. By random forest modeling, we nominated a list of urine proteins that could separate lung cancers from other cases. With a feature selection algorithm, we selected a panel of five urinary biomarkers (FTL: Ferritin light chain; MAPK1IP1L: Mitogen-Activated Protein Kinase 1 Interacting Protein 1 Like; FGB: Fibrinogen Beta Chain; RAB33B: RAB33B, Member RAS Oncogene Family; RAB15: RAB15, Member RAS Oncogene Family) and established a combinatorial model that can correctly classify the majority of lung cancer cases both in the training set (n = 46) and the test sets (n = 14–47 per set) with an AUC ranging from 0.8747 to 0.9853. A combination of five urinary biomarkers not only discriminates lung cancer patients from control groups but also differentiates lung cancer from other common tumors. The biomarker panel and the predictive model, when validated by more samples in a multi-center setting, may be used as an auxiliary diagnostic tool along with imaging technology for lung cancer detection.

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A case-control study of biomarker discovery for lung cancer diagnosis was conducted.

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Human urine profiles in control cases and cancers were characterized.

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A list of candidate biomarkers was nominated and evaluated.

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A panel of urinary biomarkers was established and tumor-specificity was evaluated.

Cancer diagnosis with a noninvasive method at the early stage of the disease is highly desirable. Here, we analyzed hundreds of human urine samples from healthy individuals, patients with benign pulmonary diseases, and 6 types of cancers by proteomics and developed a panel of five urinary proteins that can separate the lung cancer from benign pulmonary diseases as well as the other 5 cancers (bladder, cervical, colorectal, esophageal and gastric) with a good sensitivity and disease specificity. Further validation experiments with expanded sample numbers are required to investigate whether this method can be applied in a clinical setting for the diagnosis of lung cancer.

Tumor characterization by ultrasound-release of multiple protein and microRNA biomarkers, preclinical and clinical evidence

We have previously shown that low frequency ultrasound can release biomarkers from cells into the murine circulation enabling an amplification and localization of the released biomarker that could be used as a blood-based method to detect cancer earlier and monitor therapy. In this study, we further demonstrate that this technique could be used for characterization of tumors and/or identification of cellular masses of unknown origin due to the release of multiple protein and nucleic acid biomarkers in cells in culture, mice and patients. We sonicated colon (LS174T) and prostate (LNCaP) cancer cell lines in culture at a low frequency of 1 MHz and show that there were several-fold changes in multiple protein and microRNA (miRNA) abundance with treatment at various intensities and time. This release was dependent on the duration and intensity of the sonication for both cell lines. Significant increased release in biomarkers was also observed following tumor sonication in living mice bearing subcutaneous LS174T cell line xenografts (for proteins and nucleic acids) and in an experimental LS174T liver tumor model (for proteins only). Finally, we demonstrated this methodology of multiple biomarker release in patients undergoing ablation of uterine fibroids using MR guided high intensity focused ultrasound. Two protein biomarkers significantly increased in the plasma after the ultrasound treatment in 21 samples tested. This proof that ultrasound-amplification method works in soft tissue tumor models together with biomarker multiplexing, could allow for an effective non-invasive method for identification, characterization and localization of incidental lesions, cancer and other disease. Pre-treatment quantification of the biomarkers, allows for individualization of quantitative comparisons. This individualization of normal marker levels in this method allows for specificity of the biomarker-increase to each patient, tumor or organ being studied.

Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary cooperation within the PDAC community is poised to confront it.

Validation of Biomarkers for Early Detection of Pancreatic Cancer: Summary of The Alliance of Pancreatic Cancer Consortia for Biomarkers for Early Detection Workshop

Pancreatic cancer is the third leading cause of cancer death in the United States, and the 5-year relative survival for patients diagnosed with pancreatic cancer is less than 10%. Early intervention is the key to a better survival outcome. Currently, there are no biomarkers that can reliably detect pancreatic cancer at an early stage or identify precursors that are destined to progress to malignancy. The National Cancer Institute in partnership with the Kenner Family Research Fund and the Pancreatic Cancer Action Network convened a Data Jamboree on Biomarkers workshop on December 5, 2016, to discuss and evaluate existing or newly developed biomarkers and imaging methods for early detection of pancreatic cancer. The primary goal of this workshop was to determine if there are any promising biomarkers for early detection of pancreatic cancer that are ready for clinical validation. The Alliance of Pancreatic Cancer Consortia for Biomarkers for Early Detection, formed under the auspices of this workshop, will provide the common platform and the resources necessary for validation. Although none of the biomarkers evaluated seemed ready for a large-scale biomarker validation trial, a number of them had sufficiently high sensitivity and specificity to warrant additional research, especially if combined with other biomarkers to form a panel.

The Novel Oncolytic Adenoviral Mutant Ad5-3Δ-A20T Retargeted to αvβ6 Integrins Efficiently Eliminates Pancreatic Cancer Cells

Metastatic pancreatic ductal adenocarcinomas (PDAC) are incurable due to the rapid development of resistance to all current therapeutics. Oncolytic adenoviral mutants have emerged as a promising new strategy that negates such resistance. In contrast to normal tissue, the majority of PDACs express the αvβ6 integrin receptor. To exploit this feature, we modified our previously reported oncolytic adenovirus, AdΔΔ, to selectively target αvβ6 integrins to facilitate systemic delivery. Structural modifications to AdΔΔ include the expression of the small but potent αvβ6-binding peptide, A20FMDV2, and ablation of binding to the native coxsackie and adenovirus receptor (CAR) within the fiber knob region. The resultant mutant, Ad5-3Δ-A20T, infected and killed αvβ6 integrin-expressing cells more effectively than the parental wild-type (Ad5wt) virus and AdΔΔ. Viral uptake through αvβ6 integrins rather than native viral receptors (CAR, αvβ3 and αvβ5 integrins) promoted viral propagation and spread. Superior efficacy of Ad5-3Δ-A20T compared with Ad5wt was demonstrated in 3D organotypic cocultures, and similar potency between the two viruses was observed in Suit-2 in vivo models. Importantly, Ad5-3Δ-A20T infected pancreatic stellate cells at low levels, which may further facilitate viral spread and cancer cell elimination either as a single agent or in combination with the chemotherapy drug, gemcitabine. We demonstrate that Ad5-3Δ-A20T is highly selective for αvβ6 integrin-expressing pancreatic cancer cells, and with further development, this new and exciting strategy can potentially be extended to improve the systemic delivery of adenoviruses to pancreatic cancer patients. Mol Cancer Ther; 17(2); 575-87. ©2018 AACR.