Metabolites of purine nucleoside phosphorylase (NP) in serum have the potential to delineate pancreatic adenocarcinoma

Pancreatic Adenocarcinoma (PDAC), the fourth highest cause of cancer related deaths in the United States, has the most aggressive presentation resulting in a very short median survival time for the affected patients. Early detection of PDAC is confounded by lack of specific markers that has motivated the use of high throughput molecular approaches to delineate potential biomarkers. To pursue identification of a distinct marker, this study profiled the secretory proteome in 16 PDAC, 2 carcinoma in situ (CIS) and 7 benign patients using label-free mass spectrometry coupled to 1D-SDS-PAGE and Strong Cation-Exchange Chromatography (SCX). A total of 431 proteins were detected of which 56 were found to be significantly elevated in PDAC. Included in this differential set were Parkinson disease autosomal recessive, early onset 7 (PARK 7) and Alpha Synuclein (aSyn), both of which are known to be pathognomonic to Parkinson's disease as well as metabolic enzymes like Purine Nucleoside Phosphorylase (NP) which has been exploited as therapeutic target in cancers. Tissue Microarray analysis confirmed higher expression of aSyn and NP in ductal epithelia of pancreatic tumors compared to benign ducts. Furthermore, extent of both aSyn and NP staining positively correlated with tumor stage and perineural invasion while their intensity of staining correlated with the existence of metastatic lesions in the PDAC tissues. From the biomarker perspective, NP protein levels were higher in PDAC sera and furthermore serum levels of its downstream metabolites guanosine and adenosine were able to distinguish PDAC from benign in an unsupervised hierarchical classification model. Overall, this study for the first time describes elevated levels of aSyn in PDAC as well as highlights the potential of evaluating NP protein expression and levels of its downstream metabolites to develop a multiplex panel for non-invasive detection of PDAC.     

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

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

Pancreatic Cancer: Current Progress and Future Challenges

Pancreatic ductal adenocarcinoma (PDAC), the most common form of pancreatic cancer, remains one of the highly lethal malignancies. The highly refractory nature of clinically advanced disease and lack of a reliable biomarker for early detection are major obstructions in improving patient outcome. The recent efforts, however, in understanding the pancreatic tumor biology have resulted in the recognition of novel addictions as well as vulnerabilities of tumor cells and are being assessed for their clinical potential. This special issue highlights some of the recent progress, complexity and challenges towards improving disease outcome in patients with this lethal malignancy.     

Overexpression and elevated serum levels of phosphoglycerate kinase 1 in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a common malignancy with a very low 5-year survival rate. Currently, there are no valid markers for early detection and targets for therapy. Here, we used 2-DE to analyze the protein profiles of eight PDAC specimens and paired adjacent nontumor tissues. MS was used to identify 15 protein spots that were found to be overexpressed in PDAC tissues versus adjacent controls. One of them was identified as phosphoglycerate kinase (PGK) 1, a secretable glycolytic enzyme known to participate in angiogenesis. Immunohistochemical analysis of 63 PDAC specimens revealed moderate to strong expression of PGK1 in >70% of the tumors. Further Western blotting analysis of cells from tumor and adjacent nontumor tissues obtained by laser capture microdissection confirmed the enhanced expression of PGK1 in tumor cells. Furthermore, the serum levels of PGK1 were significantly higher in PDAC patients (n = 21) than in the control group (n = 25) (p < 0.005), as determined by ELISA. These observations indicate that protein profile analysis using a combination of 2-DE and MS provides an effective strategy for identifying biomarkers that may have diagnostic potential for PDAC, and identify PGK1 as a potential biomarker and/or therapeutic target for PDAC.     

Five key lncRNAs considered as prognostic targets for predicting pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, and the 5‐year survival rate was only 7.7%. To improve prognosis, a screening biomarker for early diagnosis of pancreatic cancer is in urgent need. Long non‐coding RNA (lncRNA) expression profiles as potential cancer prognostic biomarkers play critical roles in development of tumorigenesis and metastasis of cancer. However, lncRNA signatures in predicting the survival of a patient with PDAC remain unknown. In the current study, we try to identify potential lncRNA biomarkers and their prognostic values in PDAC. LncRNAs expression profiles and corresponding clinical information for 182 cases with PDAC were acquired from The Cancer Genome Atlas (TCGA). A total of 14 470 lncRNA were identified in the cohort, and 175 PDAC patients had clinical variables. We obtained 108 differential expressed lncRNA via R packages. Univariate and multivariate Cox proportional hazards regression, lasso regression was performed to screen the potential prognostic lncRNA. Five lncRNAs have been recognized to significantly correlate with OS. We established a linear prognostic model of five lncRNA (C9orf139, MIR600HG, RP5‐965G21.4, RP11‐436K8.1, and CTC‐327F10.4) and divided patients into high‐ and low‐risk group according to the prognostic index. The five lncRNAs played independent prognostic biomarkers of OS of PDAC patients and the AUC of the ROC curve for the five lncRNAs signatures prediction 5‐year survival was 0.742. In addition, targeted genes of MIR600HG, C9orf139, and CTC‐327F10.4 were explored and functional enrichment was also conducted. These results suggested that this five‐lncRNAs signature could act as potential prognostic biomarkers in the prediction of PDAC patient's survival.     

Molecular pathogenesis of pancreatic cancer: advances and challenges

Pancreatic ductal adenocarcinoma (PDAC) is still a devastating and incurable disease with a median survival of 3-6 months and a 5-year survival rate of 1-4% when all stages are considered. Although crucial advances in our understanding of the molecular pathogenesis of the disease have been made, the exceptional aggressiveness of PDAC remains largely unexplained. Some key results will probably direct future PDAC research activities. For example, recent identification of pancreatic tumor stem cells has stimulated the debate over the cell of origin. Further, powerful new genetically engineered mouse models support the concept that stepwise progression of epithelial precursor lesions leads to invasive PDAC as a result of accumulating mutations in K-ras, INK4A/ARF, TP53 and DPC4; these models accentuate the initiating function of the K-ras mutation. Established PDAC exhibits all the classic hallmarks of cancer, including self-sufficiency in growth signals, insensitivity to anti-growth signals, evasion of apoptosis, limitless replicative potential, sustained angiogenesis, tissue invasion, and metastasis. This review provides an overview of the molecular machinery that PDAC utilizes to acquire these tumorigenic capacities. Moreover, recent advances have identified essential elements of key pathways partly recapitulating developmental signals, and of the tumor microenvironment that promotes tumor growth through the complex interplay of its different cellular components. In spite of progress in molecular research, there is still a dichotomy between the encouraging results obtained with targeted interference of numerous oncogenic pathways in vitro and a lack of significant improvement in clinical detection and survival. Thus our primary challenge remains to translate the solid knowledge of genetic and epigenetic alterations in PDAC into clinical tools which can be used for early diagnosis and effective therapy.     

A combination of urinary biomarker panel and PancRISK score for earlier detection of pancreatic cancer: A case–control study

BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with around 9% of patients surviving >5 years. Asymptomatic in its initial stages, PDAC is mostly diagnosed late, when already a locally advanced or metastatic disease, as there are no useful biomarkers for detection in its early stages, when surgery can be curative. We have previously described a promising biomarker panel (LYVE1, REG1A, and TFF1) for earlier detection of PDAC in urine. Here, we aimed to establish the accuracy of an improved panel, including REG1B instead of REG1A, and an algorithm for data interpretation, the PancRISK score, in additional retrospectively collected urine specimens. We also assessed the complementarity of this panel with CA19-9 and explored the daily variation and stability of the biomarkers and their performance in common urinary tract cancers.Methods and findingsClinical specimens were obtained from multiple centres: Barts Pancreas Tissue Bank, University College London, University of Liverpool, Spanish National Cancer Research Center, Cambridge University Hospital, and University of Belgrade. The biomarker panel was assayed on 590 urine specimens: 183 control samples, 208 benign hepatobiliary disease samples (of which 119 were chronic pancreatitis), and 199 PDAC samples (102 stage I–II and 97 stage III–IV); 50.7% were from female individuals. PDAC samples were collected from patients before treatment. The samples were assayed using commercially available ELISAs. Statistical analyses were performed using non-parametric Kruskal–Wallis tests adjusted for multiple comparisons, and multiple logistic regression. Training and validation datasets for controls and PDAC samples were obtained after random division of the whole available dataset in a 1:1 ratio. The substitution of REG1A with REG1B enhanced the performance of the panel to detect resectable PDAC. In a comparison of controls and PDAC stage I–II samples, the areas under the receiver operating characteristic curve (AUCs) increased from 0.900 (95% CI 0.843–0.957) and 0.926 (95% CI 0.843–1.000) in the training (50% of the dataset) and validation sets, respectively, to 0.936 in both the training (95% CI 0.903–0.969) and the validation (95% CI 0.888–0.984) datasets for the new panel including REG1B. This improved panel showed both sensitivity (SN) and specificity (SP) to be >85%. Plasma CA19-9 enhanced the performance of this panel in discriminating PDAC I–II patients from controls, with AUC = 0.992 (95% CI 0.983–1.000), SN = 0.963 (95% CI 0.913–1.000), and SP = 0.967 (95% CI 0.924–1.000). We demonstrate that the biomarkers do not show significant daily variation, and that they are stable for up to 5 days at room temperature. The main limitation of our study is the low number of stage I–IIA PDAC samples (n = 27) and lack of samples from individuals with hereditary predisposition to PDAC, for which specimens collected from control individuals were used as a proxy.ConclusionsWe have successfully validated our urinary biomarker panel, which was improved by substituting REG1A with REG1B. At a pre-selected cutoff of >80% SN and SP for the affiliated PancRISK score, we demonstrate a clinically applicable risk stratification tool with a binary output for risk of developing PDAC (‘elevated’ or ‘normal’). PancRISK provides a step towards precision surveillance for PDAC patients, which we will test in a prospective clinical study, UroPanc.

Silvana Debernardi and colleagues establish a clinical risk score and a biomarker panel for early detection of pancreatic cancer.     

Targeted nanoparticles for imaging incipient pancreatic ductal adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) carries an extremely poor prognosis, typically presenting with metastasis at the time of diagnosis and exhibiting profound resistance to existing therapies. The development of molecular markers and imaging probes for incipient PDAC would enable earlier detection and guide the development of interventive therapies. Here we sought to identify novel molecular markers and to test their potential as targeted imaging agents.

Methods and Findings

Here, a phage display approach was used in a mouse model of PDAC to screen for peptides that specifically bind to cell surface antigens on PDAC cells. These screens yielded a motif that distinguishes PDAC cells from normal pancreatic duct cells in vitro, which, upon proteomics analysis, identified plectin-1 as a novel biomarker of PDAC. To assess their utility for in vivo imaging, the plectin-1 targeted peptides (PTP) were conjugated to magnetofluorescent nanoparticles. In conjunction with intravital confocal microscopy and MRI, these nanoparticles enabled detection of small PDAC and precursor lesions in engineered mouse models.

Conclusions

Our approach exploited a well-defined model of PDAC, enabling rapid identification and validation of PTP. The developed specific imaging probe, along with the discovery of plectin-1 as a novel biomarker, may have clinical utility in the diagnosis and management of PDAC in humans.     

Emerging technologies for salivaomics in cancer detection

Salivary diagnostics has great potential to be used in the early detection and prevention of many cancerous diseases. If implemented with rigour and efficiency, it can result in improving patient survival times and achieving earlier diagnosis of disease. Recently, extraordinary efforts have been taken to develop non‐invasive technologies that can be applied without complicated and expensive procedures. Saliva is a biofluid that has demonstrated excellent properties and can be used as a diagnostic fluid, since many of the biomarkers suggested for cancers can also be found in whole saliva, apart from blood or other body fluids. The currently accepted gold standard methods for biomarker development include chromatography, mass spectometry, gel electrophoresis, microarrays and polymerase chain reaction‐based quantification. However, salivary diagnostics is a flourishing field with the rapid development of novel technologies associated with point‐of‐care diagnostics, RNA sequencing, electrochemical detection and liquid biopsy. Those technologies will help introduce population‐based screening programs, thus enabling early detection, prognosis assessment and disease monitoring. The purpose of this review is to give a comprehensive update on the emerging diagnostic technologies and tools for the early detection of cancerous diseases based on saliva.     

RON receptor tyrosine kinase in pancreatic ductal adenocarcinoma: Pathogenic mechanism in malignancy and pharmaceutical target for therapy

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers with poor prognosis and high mortality. Molecular aberrations associated with PDAC pathogenesis and progression have been extensively investigated. Nevertheless, these findings have not been translated into clinical practice. Lack of therapeutics for PDAC treatment is another challenge. Recent application of molecularly targeted and immunoregulatory therapies appears to be disappointing. Thus, discovery of new targets and therapeutics is urgently needed to combat this malignant disease. The RON receptor tyrosine kinase is a tumorigenic determinant in PDAC malignancy, which provides the rationale to target RON for PDAC treatment. In this review, we summarize the latest evidence of RON in PDAC pathogenesis and the development of anti-RON antibody-drug conjugates for potential PDAC therapy. The finding that anti-RON antibody-drug conjugates show efficacy in preclinical animal models highlights the potential of this novel class of anti-cancer biotherapeutics in future clinical trials.     

A Six-Gene Signature Predicts Survival of Patients with Localized Pancreatic Ductal Adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal disease. For patients with localized PDAC, surgery is the best option, but with a median survival of less than 2 years and a difficult and prolonged postoperative course for most, there is an urgent need to better identify patients who have the most aggressive disease.

Methods and Findings

We analyzed the gene expression profiles of primary tumors from patients with localized compared to metastatic disease and identified a six-gene signature associated with metastatic disease. We evaluated the prognostic potential of this signature in a training set of 34 patients with localized and resected PDAC and selected a cut-point associated with outcome using X-tile. We then applied this cut-point to an independent test set of 67 patients with localized and resected PDAC and found that our signature was independently predictive of survival and superior to established clinical prognostic factors such as grade, tumor size, and nodal status, with a hazard ratio of 4.1 (95% confidence interval [CI] 1.7–10.0). Patients defined to be high-risk patients by the six-gene signature had a 1-year survival rate of 55% compared to 91% in the low-risk group.

Conclusions

Our six-gene signature may be used to better stage PDAC patients and assist in the difficult treatment decisions of surgery and to select patients whose tumor biology may benefit most from neoadjuvant therapy. The use of this six-gene signature should be investigated in prospective patient cohorts, and if confirmed, in future PDAC clinical trials, its potential as a biomarker should be investigated. Genes in this signature, or the pathways that they fall into, may represent new therapeutic targets. Please see later in the article for the Editors'' Summary     

Urinary metabolite prognostic biomarker panel for pancreatic ductal adenocarcinomas

BackgroundPatients with pancreatic ductal adenocarcinoma (PDAC) have a very low survival rate and surgical resection is the only curative intent treatment available. However, the majority of patients relapse after surgery and identification of biomarkers for accurate prognostication of PDAC patients is required. We have recently identified a six biomarker (i.e., trigonelline, glycolate, hippurate, creatine, myoinositol and hydroxyacetone) urinary metabolite panel with very high potential to diagnose PDAC (Int J Cancer 2021;148:1508–18). This study aimed to assess the prognostic ability of these previously identified diagnostic metabolites in the urine of PDAC patients.MethodsMetabolite data from 88 PDAC patients was statistically assessed for their prognostic ability.ResultsA panel of three metabolites (i.e., trigonelline, hippurate and myoinositol) was able to stratify patients with good- or poor-prognosis based on overall survival. The PDAC patients with abnormal levels of 2 or more metabolites in their urine demonstrated significantly lower survival compared to patients with abnormal levels of one or less metabolites.ConclusionThese results demonstrate that the selected three metabolite panel could be used to stratify patients based on their prognostic outcomes and if independently validated may lead to the development of a urinary prognostic biomarker test for PDAC.General significanceThis study highlights the potential of using ¹H-nuclear magnetic resonance spectroscopy for the identification of novel metabolites which can prognosticate cancer patients.     

Molecular Biomarkers of Pancreatic Intraepithelial Neoplasia and Their Implications in Early Diagnosis and Therapeutic Intervention of Pancreatic Cancer

Lack of early detection and effective interventions is a major reason for the poor prognosis and dismal survival rates for pancreatic cancer. Pancreatic intraepithelial neoplasia (PanIN) is the most common precursor of invasive pancreatic ductal adenocarcinoma (PDAC). Each stage in the progression from PanIN to PDAC is well characterized by multiple significant genetic alterations affecting signaling pathways. Understanding the biological behavior and molecular alterations in the progression from PanIN to PDAC is crucial to the identification of noninvasive biomarkers for early detection and diagnosis and the development of preventive and therapeutic strategies for control of pancreatic cancer progression. This review focuses on molecular biomarkers of PanIN and their important roles in early detection and treatment of pancreatic cancer.     

Prognostic Fifteen-Gene Signature for Early Stage Pancreatic Ductal Adenocarcinoma

The outcomes of patients treated with surgery for early stage pancreatic ductal adenocarcinoma (PDAC) are variable with median survival ranging from 6 months to more than 5 years. This challenge underscores an unmet need for developing personalized medicine strategies to refine the current treatment decision-making process. To derive a prognostic gene signature for patients with early stage PDAC, a PDAC cohort from Moffitt Cancer Center (n = 63) was used with overall survival (OS) as the primary endpoint. This was further evaluated using an independent microarray cohort dataset (Stratford et al: n = 102). Technical validation was performed by NanoString platform. A prognostic 15-gene signature was developed and showed a statistically significant association with OS in the Moffitt cohort (hazard ratio [HR] = 3.26; p<0.001) and Stratford et al cohort (HR = 2.07; p = 0.02), and was independent of other prognostic variables. Moreover, integration of the signature with the TNM staging system improved risk prediction (p<0.01 in both cohorts). In addition, NanoString validation showed that the signature was robust with a high degree of reproducibility and the association with OS remained significant in the two cohorts. The gene signature could be a potential prognostic tool to allow risk-adapted stratification of PDAC patients into personalized treatment protocols; possibly improving the currently poor clinical outcomes of these patients.     

The first decade of MALDI protein profiling: a lesson in translational biomarker research

MALDI protein profiling has identified several important challenges in omics-based biomarker research. First, research into the analytical performance of a novel omics-platform of potential diagnostic impact must be carried out in a critical manner and according to common guidelines. Evaluation studies should be performed at an early time and preferably before massive advancement into explorative biomarker research. In particular, MALDI profiling underscores the need for an adequate understanding of the causal relationship between molecular abundance and the quantitative measure in multivariate biomarker research. Secondly, MALDI profiling has raised awareness of the significant risk of false-discovery in biomarker research due to several confounding factors, including sample processing and unspecific host-response to disease. Here, the experience from MALDI profiling supports that a central challenge in unbiased molecular profiling is to pinpoint the aberrations of clinical interest among potentially massive unspecific changes that can accompany disease. The lessons from the first decade of MALDI protein profiling are relevant for future efforts in advancing omics-based biomarker research beyond the laboratory setting and into clinical verification.     

Utility of d-serine monitoring in kidney disease

d-Serine, a long-term undetected enantiomer of serine, is now showing its potential as a biomarker for kidney diseases. The intra-body dynamics of d-serine, currently defined by blood levels and urinary excretion dynamics, are useful for a comprehensive assessment of kidney function and disease activity. Thus, widespread adoption of d-serine as a biomarker can resolve the long-standing clinical challenge of the early detection and prognostic prediction of kidney diseases. Accuracy and reliability of the measurements are particularly important because these measurements will affect treatment decisions and thus impact the patient's emotional state and quality of life. Accordingly, this review focuses on current clinical challenges in kidney diseases and the potential for monitoring of d-serine to overcome these issues, and discuss the requirements of accurate quantification.     

Non-coding RNAs in pancreatic ductal adenocarcinoma: New approaches for better diagnosis and therapy

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies with a 5-year survival rate less than 8%, which has remained unchanged over the last 50 years. Early detection is particularly difficult due to the lack of disease-specific symptoms and a reliable biomarker. Multimodality treatment including chemotherapy, radiotherapy (used sparingly) and surgery has become the standard of care for patients with PDAC. Carbohydrate antigen 19–9 (CA 19–9) is the most common diagnostic biomarker; however, it is not specific enough especially for asymptomatic patients. Non-coding RNAs are often deregulated in human malignancies and shown to be involved in cancer-related mechanisms such as cell growth, differentiation, and cell death. Several micro, long non-coding and circular RNAs have been reported to date which are involved in PDAC. Aim of this review is to discuss the roles and functions of non-coding RNAs in diagnosis and treatments of PDAC.