The Use of Biomarkers in Early Diagnostics of Pancreatic Cancer

Urinary biomarkers analysis as a diagnostic tool for early detection of pancreatic adenocarcinoma: Molecular quantification approach

BACKGROUND AND AIMS

Pancreatic ductal adenocarcinoma (PDAC) is infrequent. Currently, non-invasive biomarkers for early detection of PDAC are not accessible. Here, we intended to identify a set of urine markers able to discriminate patients with early-stage PDAC from healthy individuals.

PATIENTS AND METHODS

Seventy-five urine samples from PDAC patients and 50 healthy controls were assayed using quantitative real-time PCR (qPCR). The chosen biomarkers were lymphatic vessel endothelial HA receptor (LYVE-1), regenerating islet-derived 1 alpha (REG1A), and trefoil factor family (TFF1).

RESULTS

LYVE-1, REG1A, and TFF1 expression in PDAC proved to be significantly elevated compared to healthy individuals (p < 0.05). Determination of these markers' expression might be useful for early tumor diagnosis with a sensitivity of 96 %, 100 %, and 73.33 % respectively, and a specificity of 100 %, 82 %, and 100 % respectively.

CONCLUSION

We have recognized three diagnostic biomarkers REG1A, TFF1, and LYVE1 that can detect patients with early-stage pancreatic cancer in non-invasive urine specimens with improved sensitivity and specificity. To the best of our knowledge, there have been no prior investigations examining the mRNA expression levels of them in urine within the Egyptian population.

Darifenacin: a promising chitinase 3-like 1 inhibitor to tackle drug resistance in pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) is among the most aggressive malignancies. Our previous work revealed Chitinase 3-like 1 (CHI3L1) involvement in PDAC resistance to gemcitabine, identifying it as a promising therapeutic target. Here, we aimed to identify putative CHI3L1 inhibitors and to investigate their chemosensitizing potential in PDAC.

METHODS

Docking analysis for CHI3L1 identified promising CHI3L1 inhibitors, including darifenacin (muscarinic receptor antagonist). PDAC cell lines (BxPC-3, PANC-1) and primary PDAC cells were used to evaluate darifenacin's effects on cell growth (Sulforhodamine B, SRB), alone or in combination with gemcitabine or gemcitabine plus paclitaxel. Cytotoxicity against normal immortalized pancreatic ductal cells (HPNE) was assessed. Recombinant protein was used to confirm the impact of darifenacin on CHI3L1-induced PDAC cellular resistance to therapy (SRB assay). Darifenacin's effect on Akt activation was analysed by ELISA. The association between cholinergic receptor muscarinic 3 (CHRM3) expression and therapeutic response was evaluated by immunohistochemistry of paraffin-embedded tissues from surgical resections of a 68 patients' cohort.

RESULTS

In silico screening revealed the ability of darifenacin to target CHI3L1 with high efficiency. Darifenacin inhibited PDAC cell growth, with a GI50 of 26 and 13.6 µM in BxPC-3 and PANC-1 cells, respectively. These results were confirmed in primary PDAC-3 cells, while darifenacin showed no cytotoxicity against HPNE cells. Importantly, darifenacin sensitized PDAC cells to standard chemotherapies, reverted CHI3L1-induced PDAC cellular resistance to therapy, and decreased Akt phosphorylation. Additionally, high CHMR3 expression was associated with low therapeutic response to gemcitabine.

CONCLUSION

This work highlights the potential of darifenacin as a chemosensitizer for PDAC treatment.

Decoding the Intricate Landscape of Pancreatic Cancer: Insights into Tumor Biology, Microenvironment, and Therapeutic Interventions

Pancreatic ductal adenocarcinoma (PDAC) presents significant oncological challenges due to its aggressive nature and poor prognosis. The tumor microenvironment (TME) plays a critical role in progression and treatment resistance. Non-neoplastic cells, such as cancer-associated fibroblasts (CAFs) and tumor-associated macrophages (TAMs), contribute to tumor growth, angiogenesis, and immune evasion. Although immune cells infiltrate TME, tumor cells evade immune responses by secreting chemokines and expressing immune checkpoint inhibitors (ICIs). Vascular components, like endothelial cells and pericytes, stimulate angiogenesis to support tumor growth, while adipocytes secrete factors that promote cell growth, invasion, and treatment resistance. Additionally, perineural invasion, a characteristic feature of PDAC, contributes to local recurrence and poor prognosis. Moreover, key signaling pathways including Kirsten rat sarcoma viral oncogene (KRAS), transforming growth factor beta (TGF-β), Notch, hypoxia-inducible factor (HIF), and Wnt/β-catenin drive tumor progression and resistance. Targeting the TME is crucial for developing effective therapies, including strategies like inhibiting CAFs, modulating immune response, disrupting angiogenesis, and blocking neural cell interactions. A recent multi-omic approach has identified signature genes associated with anoikis resistance, which could serve as prognostic biomarkers and targets for personalized therapy.

Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis

BACKGROUND

Machine Learning (ML) plays a crucial role in biomedical research. Nevertheless, it still has limitations in data integration and irreproducibility. To address these challenges, robust methods are needed. Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive cancer with low early detection rates and survival rates, is used as a case study. PDAC lacks reliable diagnostic biomarkers, especially metastatic biomarkers, which remains an unmet need. In this study, we propose an ML-based approach for discovering disease biomarkers, apply it to the identification of a PDAC metastatic composite biomarker candidate, and demonstrate the advantages of harnessing data resources.

METHODS

We utilised primary tumour RNAseq data from five public repositories, pooling samples to maximise statistical power and integrating data by correcting for technical variance. Data were split into train and validation sets. The train dataset underwent variable selection via a 10-fold cross-validation process that combined three algorithms in 100 models per fold. Genes found in at least 80% of models and five folds were considered robust to build a consensus multivariate model. A random forest model was constructed using selected genes from the train dataset and tested in the validation set. We also assessed the goodness of prediction by recalibrating a model using only the validation data. The biological context and relevance of signals was explored through enrichment and pathway analyses using QIAGEN Ingenuity Pathway Analysis and GeneMANIA.

RESULTS

We developed a pipeline that can detect robust signatures to build composite biomarkers. We tested the pipeline in PDAC, exploiting transcriptomics data from different sources, proposing a composite biomarker candidate comprised of fifteen genes consistently selected that showed very promising predictive capability. Biological contextualisation revealed links with cancer progression and metastasis, underscoring their potential relevance. All code is available in GitHub.

CONCLUSION

This study establishes a robust framework for identifying composite biomarkers across various disease contexts. We demonstrate its potential by proposing a plausible composite biomarker candidate for PDAC metastasis. By reusing data from public repositories, we highlight the sustainability of our research and the wider applications of our pipeline. The preliminary findings shed light on a promising validation and application path.

Interrogating Matrix Stiffness and Metabolomics in Pancreatic Ductal Carcinoma Using an Openable Microfluidic Tumor-on-a-Chip

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense fibrotic stroma that contributes to aggressive tumor biology and therapeutic resistance. Current in vitro PDAC models lack sufficient optical and physical access for fibrous network visualization, in situ mechanical stiffness measurement, and metabolomic profiling. Here, we describe an openable multilayer microfluidic PDAC-on-a-chip platform that consists of pancreatic tumor cells (PTCs) and pancreatic stellate cells (PSCs) embedded in a 3D collagen matrix that mimics the stroma. Our system allows fibrous network visualization via reflected light confocal (RLC) microscopy, in situ mechanical stiffness testing using atomic force microscopy (AFM), and compartmentalized hydrogel extraction for PSC metabolomic profiling via mass spectrometry (MS) analysis. In comparing cocultures of gel-embedded PSCs and PTCs with PSC-only monocultures, RLC microscopy identified a significant decrease in pore size and corresponding increase in fiber density. In situ AFM indicated significant increases in stiffness, and hallmark characteristics of PSC activation were observed using fluorescence microscopy. PSCs in coculture also demonstrated localized fiber alignment and densification as well as increased collagen production. Finally, an untargeted MS study putatively identified metabolic contributions consistent with in vivo PDAC studies. Taken together, this platform can potentially advance our understanding of tumor-stromal interactions toward the discovery of novel therapies.

The role of abdominal ultrasonography in patients with isoattenuating pancreatic carcinoma

AIMS

The main objective of this study was to determine the sensitivity of abdominal ultrasonography (US) in patients with isoattenuating pancreatic carcinoma and to compare the frequency of secondary signs on abdominal US and endoscopic ultrasonography (EUS) in these tumours.

METHODS

Twenty-four patients with histologically or cytologically verified isoattenuating pancreatic carcinoma who underwent abdominal US, contrast-enhanced CT and EUS of the pancreas as part of the diagnostic workup were included in this retrospective study. The sensitivity of abdominal US in detecting the isoattenuating pancreatic carcinoma was investigated and the frequency of secondary signs of isoattenuating pancreatic carcinoma on abdominal US and EUS was compared.

RESULTS

In 5 of 24 patients (21%) with isoattenuating pancreatic carcinoma, a hypoechogenic pancreatic lesion was directly visualised on abdominal US. Secondary signs were present on US in 21 patients (88%). These included dilatation of the common bile duct and/or intrahepatic bile ducts in 19/24 (79%), dilatation of the pancreatic duct in 3/24 (13%), abnormal contour/inhomogeneity of the pancreas in 1/24 (4%), and atrophy of the distal parenchyma in 1/24 (4%). Pancreatic duct dilatation was observed more frequently on EUS than on abdominal US (P=0.002). For other secondary signs, there was no significant difference in their detection on abdominal US and EUS (P=0.61-1.00).

CONCLUSION

Abdominal US is capable of detecting secondary signs of isoattenuating pancreatic carcinoma with high sensitivity and has the potential to directly visualise these tumours.

Circulating MicroRNAs as Noninvasive Diagnostic and Prognostic Biomarkers in Pancreatic Cancer: A Review

Pancreatic cancer (PC) is one of the most lethal human cancers. Currently, most PC cases are diagnosed at an already advanced stage. Early detection of PC is critical to improving survival rates. Therefore, there is an urgent need to identify biomarkers for the early detection of PC. Recently, circulating miRNAs in whole blood and other body fluids have been reported as promising biomarkers for the early detection of various cancers, including PC. Furthermore, due to minimal invasiveness and technical availability, circulating miRNAs hold promise for further wide usage. As a potential novel molecular marker, circulating miRNAs not only represent promising noninvasive diagnostic and prognostic tools but could also improve the evaluation of tumor classification, metastasis, and curative effect. The purpose of this review is to outline the available information regarding circulating miRNAs as biomarkers for the early detection of PC.

Holistic Understanding of the Role of Carbohydrate Antigen 19-9 in Pancreatic Cancer Screening, Early Diagnosis, and Prognosis: A Systematic Review

Pancreatic ductal adenocarcinoma (PDAC) is a significant challenge due to its silent progression and well-advanced, unresectable, complicated presentation. Detecting this disease early on is crucial, and researchers have been investigating various potential biological markers, such as carbohydrate antigen 19-9 (CA 19-9), hoping to find indicators that can aid in its early detection. The primary focus of this review is on the diagnostic usefulness of CA 19-9 in detecting pancreatic cancer (PC) in the beginning stage and its usefulness in predicting progression. The database search of articles from PubMed, PMC, the Cochrane Library, and Google Scholar identified 227 articles published from 2013 to 2023. The keyword mix used in the search technique included terms like "CA 19-9," "pancreatic cancer," "diagnosis," and "early detection." This study provides evidence of CA 19-9's ability in detecting PDAC in the pre-diagnostic stage. But since the outcomes were inconsistent among the included trials, further analysis is required to develop standardized diagnostic criteria and methodologies. Furthermore, because of the variability of the study, it is not easy to make firm conclusions on CA 19-9's sensitivity as well as specificity in the first stage of pancreatic neoplasm. This in-depth overview of the available literature provides new insights into using CA 19-9 as a biological marker for detecting undiagnosed PC before progressing into the advanced stage, and was proven beneficial. However, this has to be shown in broader research with adequate sample size. Although it shows promise as a diagnostic tool, further study is required to confirm these findings.

Stratifying Risk for Pancreatic Cancer by Multiplexed Blood Test

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease, for which mortality closely parallels incidence. So far, the available techniques for PDAC detection are either too invasive or not sensitive enough. To overcome this limitation, here we present a multiplexed point-of-care test that provides a "risk score" for each subject under investigation, by combining systemic inflammatory response biomarkers, standard laboratory tests, and the most recent nanoparticle-enabled blood (NEB) tests. The former parameters are routinely evaluated in clinical practice, whereas NEB tests have been recently proven as promising tools to assist in PDAC diagnosis. Our results revealed that PDAC patients and healthy subjects can be distinguished accurately (i.e., 88.9% specificity, 93.6% sensitivity) by the presented multiplexed point-of-care test, in a quick, non-invasive, and highly cost-efficient way. Furthermore, the test allows for the definition of a "risk threshold", which can help clinicians to trace the optimal diagnostic and therapeutic care pathway for each patient. For these reasons, we envision that this work may accelerate progress in the early detection of PDAC and contribute to the design of screening programs for high-risk populations.

Role of epigenetics in pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, associated with poor survival outcomes. Lack of early diagnosis, resistance to conventional therapeutic treatments (including immunotherapy) and recurrence are some of the major hurdles in PDAC and contribute to its poor survival rate. While the risk of genetic predisposition to cancers is widely acknowledged and understood, recent advances in whole-genome and next-generation sequencing techniques have led to the acknowledgment of the role played by epigenetics, especially in PDAC. Epigenetic changes are heritable genetic modifications that influence gene expression without altering the DNA sequence. Epigenetic mechanisms (e.g., DNA methylation, post-translational modification of histone complexes and ncRNA) that result in reversible changes in gene expression are increasingly understood to be responsible for tumor initiation, development and even escape from immune surveillance. Our review seeks to highlight the various components of the epigenetic machinery that are known to be implicated in PDAC initiation and development and the feasibility of targeting these components to identify novel pharmacological strategies that could potentially lead to breakthroughs in PDAC treatment.

A decade's experience of managing suspected pancreatic adenocarcinoma at a tertiary cancer center

Background

We present our experience and established management strategy for endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) in diagnosing suspected pancreatic neoplasms at a tertiary referral cancer hospital.

Method

Relevant data were extracted from our database for patients who underwent EUS-FNA for suspected pancreatic neoplasms at our institution between 2007 and 2016.

Results

Among the 309 patients, the median age was 67 years and 56% were men. The most common presenting symptoms were abdominal pain (37%) and jaundice (29%). Concordance between radiographic diagnosis and final pathology was 89%. The mean lesion size was 34.9 mm on computed tomography and 31.5 mm on EUS. There were 197 patients (64%) with localized disease, of whom 115 (58%) had resectable lesions, 61 (31%) had borderline resectable, and 21 (11%) had unresectable lesions (mean CA 19-9 levels 1705 U/mL, 2490 U/mL, and 479 U/mL, respectively). A median of 3 FNA passes were performed to establish a pathologic diagnosis. Two patients (1%) had postprocedural adverse events. Median overall survival was 47 months in those who underwent surgery after EUS and 12 months in those who did not (P<0.001).

Conclusions

A multidisciplinary approach is employed for management of suspected pancreatic neoplasm at our tertiary cancer center. A combination of cross-sectional imaging and EUS-FNA serves as a highly effective duo in establishing a tissue diagnosis and staging with a low adverse event rate. Counterintuitively, CA 19-9 is not necessarily higher with resectable lesions than with unresectable lesions, indicating the limitation of CA 19-9 as a pancreatic tumor marker.

Diagnosis of Pancreatic Cancer Using miRNA30e Biosensor

This work describes miRNA-based electrochemical biosensor for detection of miRNA30e, a pancreatic cancer biomarker. The screen-printed gold electrode was functionalized using cysteine hydrochloride followed by immobilization of synthesized colloidal gold nanorods (10-12 nm diameter and 25-65 nm length). The gold nanorods modified electrode surface was amino functionalized for covalent attachment of single-stranded DNA probe against miRNA30e (miR30e). This platform was utilized for electrochemical measurements and response analysis of target miRNA30e. Electrochemical impedance spectroscopic measurements showed very poor sensitivity (13.51 Ω/µg/mL/cm²) using charge transfer resistance calibration plots. Cyclic voltammetry and differential pulse voltammetry-based miR30e quantification showed decreasing current response with increasing concentration of miR30e with detection range of 0.1 fg/mL-0.1 µg/mL (14.9 aM-14.9 nM). The sensitivity of DPV sensing (104.4 µA/µg/mL/cm²) was found to be 1.3 times higher than that of CV-based quantification (79.6 µA/µg/mL/cm²). miRNA-based biosensors have the potential of replacing current invasive, time consuming and technically difficult diagnostic procedures. Furthermore, the lower limit of detection of 14.9 aM miRNA30e makes it a promising tool for detection of cancer at early stages and hence increasing survival rate.

Diagnostic Utility of Serum IgG4 in Autoimmune Pancreatitis: An Updated Comprehensive Systematic Review and Meta-analysis

OBJECTIVES

Despite many studies suggesting an association between serum immunoglobulin G4 (sIgG4) and autoimmune pancreatitis (AIP), the evidence of utility in differentiation between AIP and pancreatic cancer (PC) remain uncertain.

METHODS

The analysis based on published studies. Data were pooled by means of a random-effects model, and sensitivity, specificity, diagnostic odds ratios (DOR), areas under summary receiver operating characteristic curves were calculated.

RESULTS

In the included thirteen studies, sIgG4 were measured in 594 patients with AIP and 958 patients with PC. The pooled sensitivity, specificity, DOR, and area under the curve were 0.72 [95% confidence interval (CI): 0.68-0.75], 0.93 (95% CI: 0.92-0.95), 51.37 (95% CI: 23.20-113.74), and 0.91 (95% CI: 0.87-0.95). Subgroup analyses of the DORs for region and year: Asia, (112.10; 95% CI: 27.72-453.32), non-Asia (26.01; 95% CI: 12.38-54.65), and year before 2011 (107.61; 95% CI: 39.30-294.68), year after 2011 (26.96; 95% CI: 9.78-74.32). Overall, sIgG4 was associated with AIP, the result revealed a moderate sensitivity 0.72 and high specificity 0.93. In the meta-analysis, the pooled DOR of sIgG4 levels of 2-fold upper limit 50.44 was similar with the DOR 51.37 when 1-fold cut-off value, but the summary receiver operating characteristic was 0.755 and 0.91. The higher specificity (from 93% to 98%) derived from the cut-off value (from 130-140 to 260-280 mg/dL) for sIgG4 occurred at a significant reduction in sensitivity (from 72% to 43%).

CONCLUSIONS

The study revealed sIgG4 is a good marker of AIP. Screening of sIgG4 may help clinicians differentiate between AIP and PC, and the best cut-off value should be 140 rather than 280 mg/dL.

Current Screening Strategies for Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is a dreaded malignancy with a dismal 5-year survival rate despite maximal efforts on optimizing treatment strategies. Radical surgery is the only potential curative procedure. Unfortunately, the majority of patients are diagnosed with locally advanced or metastatic disease, which renders them ineligible for curative resection. Early detection of PDAC is thus considered to be the most effective way to improve survival. In this regard, pancreatic screening has been proposed to improve results by detecting asymptomatic stages of PDAC and its precursors. There is now evidence of benefits of systematic surveillance in high-risk individuals, and the current guidelines emphasize the potential of screening to affect overall survival in individuals with genetic susceptibility syndromes or familial occurrence of PDAC. Here we aim to summarize the current knowledge about screening strategies for PDAC, including the latest epidemiological data, risk factors, associated hereditary syndromes, available screening modalities, benefits, limitations, as well as management implications.

ID1 marks the tumorigenesis of pancreatic ductal adenocarcinoma in mouse and human

Pancreatic Ductal Adenocarcinoma (PDAC) is a deadly disease that has an increasing death rate but no effective treatment to now. Although biological and immunological hallmarks of PDAC have been frequently reported recently, early detection and the particularly aggressive biological features are the major challenges remaining unclear. In the current study, we retrieved multiple scRNA-seq datasets and illustrated the genetic programs of PDAC development in genetically modified mouse models. Notably, the transcription levels of Id1 were elevated specifically along with the PDAC development. Pseudotime trajectory analysis revealed that Id1 was closely correlated with the malignancy of PDAC. The gene expression patterns of human PDAC cells were determined by the comparative analysis of the scRNA-seq data on human PDAC and normal pancreas tissues. ID1 levels in human PDAC cancer cells were dramatically increased compared to normal epithelial cells. ID1 deficiency in vitro significantly blunt the invasive tumor-formation related phenotypes. IPA analysis on the differentially expressed genes suggested that EIF2 signaling was the core pathway regulating the development of PDAC. Blocking EFI2 signaling remarkably decreased the expression of ID1 and attenuated the tumor-formation related phenotypes. These observations confirmed that ID1 was regulated by EIF2 signaling and was the critical determinator of PDAC development and progression. This study suggests that ID1 is a potential malignant biomarker of PDAC in both mouse models and human and detecting and targeting ID1 may be a promising strategy to treat or even rescue PDAC.

Prognostic role of IRS-4 in the survival of patients with pancreatic cancer

Pancreatic cancer is a malignancy of rising incidence, especially in developed countries due to causes such as sedentary lifestyles, tobacco smoking and ultraprocessed high fat and high sugar diets, amongst others. It is in fact the 7th cause of cancer-related deaths worldwide, and, in the following years, it is expected to climb upwards to 2nd position, after lung cancer. This is because it may have an asymptomatic course, and when it becomes evident it is in advanced stages, accompanied by metastasis generally. For this reason, survival rates are so low and, even in the few successful cases there is a high possibility of recurrence. Identifying new molecular biomarkers is arising as a highly useful tool for pancreatic cancer clinical management, although much research and work remain to be done in this field. Thus, the present study aims to analyze a series of molecules (IRS-4, Rb1, Ki-67 y COX-2) as candidates for prognosis and survival by immunohistochemistry techniques. Additionally, a 60-month longitudinal surveillance program was conducted, associated with diverse clinical parameters. Kaplan-Meier curves estimating the time of survival according to tumoral expression of those molecules denoted a low cumulative survival rate. Importantly, we observed that high levels of IRS-4 were significantly associated with a bad prognosis of the disease, increasing 160 times the mortality risk. In this way, our research showed a relevant value of these biomarkers in pancreatic cancer patients' survival, opening a pathway for future research areas designed to inhibit these components.

Oncogenomic Changes in Pancreatic Cancer and Their Detection in Stool

Pancreatic cancer (PC) is an aggressive malignancy with a dismal prognosis. To improve patient survival, the development of screening methods for early diagnosis is pivotal. Oncogenomic alterations present in tumor tissue are a suitable target for non-invasive screening efforts, as they can be detected in tumor-derived cells, cell-free nucleic acids, and extracellular vesicles, which are present in several body fluids. Since stool is an easily accessible source, which enables convenient and cost-effective sampling, it could be utilized for the screening of these traces. Herein, we explore the various oncogenomic changes that have been detected in PC tissue, such as chromosomal aberrations, mutations in driver genes, epigenetic alterations, and differentially expressed non-coding RNA. In addition, we briefly look into the role of altered gut microbiota in PC and their possible associations with oncogenomic changes. We also review the findings of genomic alterations in stool of PC patients, and the potentials and challenges of their future use for the development of stool screening tools, including the possible combination of genomic and microbiota markers.

Magnetic Levitation of Personalized Nanoparticle-Protein Corona as an Effective Tool for Cancer Detection

Unprecedented opportunities for early stage cancer detection have recently emerged from the characterization of the personalized protein corona (PC), i.e., the protein cloud that surrounds nanoparticles (NPs) upon exposure to a patients’ bodily fluids. Most of these methods require “direct characterization” of the PC., i.e., they necessitate protein isolation, identification, and quantification. Each of these steps can introduce bias and affect reproducibility and inter-laboratory consistency of experimental data. To fulfill this gap, here we develop a nanoparticle-enabled blood (NEB) test based on the indirect characterization of the personalized PC by magnetic levitation (MagLev). The MagLev NEB test works by analyzing the levitation profiles of PC-coated graphene oxide (GO) NPs that migrate along a magnetic field gradient in a paramagnetic medium. For the test validation, we employed human plasma samples from 15 healthy individuals and 30 oncological patients affected by four cancer types, namely breast cancer, prostate cancer, colorectal cancer, and pancreatic ductal adenocarcinoma (PDAC). Over the last 15 years prostate cancer, colorectal cancer, and PDAC have continuously been the second, third, and fourth leading sites of cancer-related deaths in men, while breast cancer, colorectal cancer, and PDAC are the second, third and fourth leading sites for women. This proof-of-concept investigation shows that the sensitivity and specificity of the MagLev NEB test depend on the cancer type, with the global classification accuracy ranging from 70% for prostate cancer to an impressive 93.3% for PDAC. We also discuss how this tool could benefit from several tunable parameters (e.g., the intensity of magnetic field gradient, NP type, exposure conditions, etc.) that can be modulated to optimize the detection of different cancer types with high sensitivity and specificity.

Dielectrophoresis-Based Biosensor for Detection of the Cancer Biomarkers CEA and CA 242 in Serum

We show that dielectrophoresis (DEP) spectroscopy is an effective transduction mechanism for detection of the concentration levels of the pancreatic cancer biomarkers cancer antigen (CA) 242 and carcinoembryonic antigen (CEA) in serum. We noticed a frequency dependence of the negative DEP force applied by interdigitated electrodes on functionalized polystyrene microspheres (PM) with respect to changes in the number of these cancer antigens bound to the PM. An electrode array with a well-defined gradient of the electric field was designed and used, which enabled the automation of the signal processing and reproducibility of the signal acquired by the biosensor.

A Comprehensive Review of the Current and Future Role of the Microbiome in Pancreatic Ductal Adenocarcinoma

Simple Summary

This review summarizes the current literature related to the microbiome and pancreatic ductal adenocarcinoma (PDAC). The aim of this review is to explore the current role of the microbiome in the disease process, screening/diagnostics and to postulate the future role with regards to therapeutic strategies including chemotherapy, immunotherapy and surgery. We further explore the future of microbiome modulation (faecal microbiome transplants, bacterial consortiums, anti-microbials and probiotics), their applications and how we can improve the future of microbiome modulation in a bid to improve PDAC outcomes.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is expected to become the second most common cause of cancer death in the USA by 2030, yet progress continues to lag behind that of other cancers, with only 9% of patients surviving beyond 5 years. Long-term survivorship of PDAC and improving survival has, until recently, escaped our understanding. One recent frontier in the cancer field is the microbiome. The microbiome collectively refers to the extensive community of bacteria and fungi that colonise us. It is estimated that there is one to ten prokaryotic cells for each human somatic cell, yet, the significance of this community in health and disease has, until recently, been overlooked. This review examines the role of the microbiome in PDAC and how it may alter survival outcomes. We evaluate the possibility of employing microbiomic signatures as biomarkers of PDAC. Ultimately this review analyses whether the microbiome may be amenable to targeting and consequently altering the natural history of PDAC.

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). However, patients afflicted with pancreatic ductal carcinoma (PDAC), one of the deadliest malignancies, overwhelmingly exhibit negative responses to checkpoint therapy. We sought to combine data analysis and machine learning to differentiate the putative mechanisms of BCC and PDAC non-response. We discover that increased MHC-I expression in malignant cells and suppression of MHC and PD-1/PD-L expression in CD8⁺ T cells is associated with nonresponse to treatment. Furthermore, we leverage machine learning to predict response to PD-1 blockade on a cellular level. We confirm divergent resistance mechanisms between BCC, PDAC, and melanoma and highlight the potential for rapid and affordable testing of gene expression in BCC patients to accurately predict response to checkpoint therapies. Our findings present an optimistic outlook for the use of quantitative cross-cancer analyses in characterizing immune responses and predicting immunotherapy outcomes.

Current trends in the diagnosis of pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a dreaded malignancy with a dismal 5-year survival rate despite maximal efforts on optimizing treatment strategies. Currently, early detection is considered to be the most effective way to improve survival as radical resection is the only potential cure. PDAC is often divided into four categories based on the extent of disease: resectable, borderline resectable, locally advanced, and metastatic. Unfortunately, the majority of patients are diagnosed with locally advanced or metastatic disease, which renders them ineligible for curative resection. This is mainly due to the lack of or vague symptoms while the disease is still localized, although appropriate utilization and prompt availability of adequate diagnostic tools is also critical given the aggressive nature of the disease. A cost-effective biomarker with high specificity and sensitivity allowing early detection of PDAC without the need for advanced or invasive methods is still not available. This leaves the diagnosis dependent on radiodiagnostic methods or endoscopic ultrasound. Here we summarize the latest epidemiological data, risk factors, clinical manifestation, and current diagnostic trends and implications of PDAC focusing on serum biomarkers and imaging modalities. Additionally, up-to-date management and therapeutic algorithms are outlined.

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

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

Metastatic pancreatic cancer: Mechanisms and detection (Review)

Pancreatic cancer (PC) is a lethal malignancy. Its prevalence rate remains low but continues to grow each year. Among all stages of PC, metastatic PC is defined as late-stage (stage IV) PC and has an even higher fatality rate. Patients with PC do not have any specific clinical manifestations. Most cases are inoperable at the time-point of diagnosis. Prognosis is also poor even with curative-intent surgery. Complications during surgery, postoperative pancreatic fistula and recurrence with metastatic foci make the management of metastatic PC difficult. While extensive efforts were made to improve survival outcomes, further elucidation of the molecular mechanisms of metastasis poses a formidable challenge. The present review provided an overview of the mechanisms of metastatic PC, summarizing currently known signaling pathways (e.g. epithelial-mesenchymal transition, NF-κB and KRAS), imaging that may be utilized for early detection and biomarkers (e.g. carbohydrate antigen 19-9, prostate cancer-associated transcript-1, F-box/LRR-repeat protein 7 and tumor stroma), giving insight into promising therapeutic targets.

Clinical Data Prediction Model to Identify Patients With Early-Stage Pancreatic Cancer

PURPOSE

Pancreatic cancer is an aggressive malignancy with patients often experiencing nonspecific symptoms before diagnosis. This study evaluates a machine learning approach to help identify patients with early-stage pancreatic cancer from clinical data within electronic health records (EHRs).

MATERIALS AND METHODS

From the Optum deidentified EHR data set, we identified early-stage (n = 3,322) and late-stage (n = 25,908) pancreatic cancer cases over 40 years of age diagnosed between 2009 and 2017. Patients with early-stage pancreatic cancer were matched to noncancer controls (1:16 match). We constructed a prediction model using eXtreme Gradient Boosting (XGBoost) to identify early-stage patients on the basis of 18,220 features within the EHR including diagnoses, procedures, information within clinical notes, and medications. Model accuracy was assessed with sensitivity, specificity, positive predictive value, and the area under the curve.

RESULTS

The final predictive model included 582 predictive features from the EHR, including 248 (42.5%) physician note elements, 146 (25.0%) procedure codes, 91 (15.6%) diagnosis codes, 89 (15.3%) medications, and 9 (1.5%) demographic features. The final model area under the curve was 0.84. Choosing a model cut point with a sensitivity of 60% and specificity of 90% would enable early detection of 58% late-stage patients with a median of 24 months before their actual diagnosis.

CONCLUSION

Prediction models using EHR data show promise in the early detection of pancreatic cancer. Although widespread use of this approach on an unselected population would produce high rates of false-positive tests, this technique may be rapidly impactful if deployed among high-risk patients or paired with other imaging or biomarker screening tools.

The Microbiome as a Potential Target for Therapeutic Manipulation in Pancreatic Cancer

Simple Summary

Pancreatic cancer is one of the most lethal cancers. It is a difficult cancer to treat, and the complexity surrounding the pancreatic tumour is one of the contributing factors. The microbiome is the collection of microorganisms within an environment and its genetic material. They reside on body surfaces and most abundantly within the human gut in symbiotic balance with their human host. Disturbance in the balance can lead to many diseases, including cancers. Significant advances have been made in cancer treatment since the introduction of immunotherapy, and the microbiome may play a part in the outcome and survival of patients with cancer, especially those treated with immunotherapy. Immunotherapy use in pancreatic cancer remains challenging. This review will focus on the potential interaction of the microbiome with pancreas cancer and how this could be manipulated.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers and is projected to be the second most common cause of cancer-related death by 2030, with an overall 5-year survival rate between 7% and 9%. Despite recent advances in surgical, chemotherapy, and radiotherapy techniques, the outcome for patients with PDAC remains poor. Poor prognosis is multifactorial, including the likelihood of sub-clinical metastatic disease at presentation, late-stage at presentation, absence of early and reliable diagnostic biomarkers, and complex biology surrounding the extensive desmoplastic PDAC tumour micro-environment. Microbiota refers to all the microorganisms found in an environment, whereas microbiome is the collection of microbiota and their genome within an environment. These organisms reside on body surfaces and within mucosal layers, but are most abundantly found within the gut. The commensal microbiome resides in symbiosis in healthy individuals and contributes to nutritive, metabolic and immune-modulation to maintain normal health. Dysbiosis is the perturbation of the microbiome that can lead to a diseased state, including inflammatory bowel conditions and aetiology of cancer, such as colorectal and PDAC. Microbes have been linked to approximately 10% to 20% of human cancers, and they can induce carcinogenesis by affecting a number of the cancer hallmarks, such as promoting inflammation, avoiding immune destruction, and microbial metabolites can deregulate host genome stability preceding cancer development. Significant advances have been made in cancer treatment since the advent of immunotherapy. The microbiome signature has been linked to response to immunotherapy and survival in many solid tumours. However, progress with immunotherapy in PDAC has been challenging. Therefore, this review will focus on the available published evidence of the microbiome association with PDAC and explore its potential as a target for therapeutic manipulation.

Increased levels of circulating circular RNA (hsa_circ_0013587) may serve as a novel biomarker for pancreatic cancer

Aim: Circular RNA can serve as a biomarker for early diagnosis of pancreatic cancer. Materials & methods: Analyzed the expression of various differentially expressed circular RNAs in the pancreatic cancer tissues by gene chip and identified the expression of hsa_circ_0013587 in pancreatic cancer cells, tissues and plasma by quantitative reverse transcription PCR (qRT-PCR). Results: Hsa_circ_0013587 was highly expressed in the pancreatic cancer tissues, cell lines and plasma samples from patients with pancreatic cancer. Notably, hsa_circ_0013587 was upregulated in pancreatic cancer patients with later clinical stages III-IV as compared with those detected in early clinical stages I-II. Conclusion: A high expression of hsa_circ_0013587 may serve as a novel diagnostic and therapeutic biomarker for pancreatic cancer.

Mebendazole disrupts stromal desmoplasia and tumorigenesis in two models of pancreatic cancer

The five-year survival rate for metastatic pancreatic cancer is currently only 3%, which increases to 13% with local invasion only and to 39% with localized disease at diagnosis. Here we evaluated repurposed mebendazole, an approved anthelminthic drug, to determine how mebendazole might work at the different stages of pancreatic cancer formation and progression. We asked if mebendazole could prevent initiation of pancreatic intraepithelial neoplasia precursor lesions, interfere with stromal desmoplasia, or suppress tumor growth and liver metastasis. In both the Kras ^LSL.G12D/+; Pdx1-Cre (KC) mouse model of caerulein-induced inflammatory pancreatitis and the Kras ^LSL.G12D/+; Tp53 ^R172H/+; Pdx1-Cre (KPC) mouse model of advanced pancreatic cancer, mebendazole significantly reduced pancreas weight, dysplasia and intraepithelial neoplasia formation, compared to controls. Mebendazole significantly reduced trichrome-positive fibrotic connective tissue and α-SMA-positive activated pancreatic stellate cells that heralds fibrogenesis. In the aggressive KPC model, mebendazole significantly suppressed pancreatic tumor growth, both as an early and late intervention. Mebendazole reduced the overall incidence of pancreatic cancer and severity of liver metastasis in KPC mice. Using early models of pancreatic cancer, treatment with mebendazole resulted in less inflammation, decreased dysplasia, with the later stage model additionally showing a decreased tumor burden, less advanced tumors, and a reduction of metastasis. We conclude that mebendazole should be investigated further as a component of adjuvant therapy to slow progression and prevent metastasis, and well as for primary prevention in the highest risk patients.

Biomarkers for early detection of pancreatic cancer - miRNAs as a potential diagnostic and therapeutic tool?

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies, with poor prognosis resulting mostly from late diagnosis. Surgery remains the most effective treatment and early detection significantly increases the overall survival. Biomarkers used for diagnosis and to monitor the response to treatment, such as carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA), are not adequate as early detection markers of PDAC, partly due to low sensitivity/specificity. Therefore, new biomarkers for PDAC are critically needed. This review aims at recent advancements in the identification and characterization of new biomarkers, microRNAs, which might prove useful in the early detection of PDAC.

Overcoming chemoresistance by targeting reprogrammed metabolism: the Achilles' heel of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death due to its late diagnosis that removes the opportunity for surgery and metabolic plasticity that leads to resistance to chemotherapy. Metabolic reprogramming related to glucose, lipid, and amino acid metabolism in PDAC not only enables the cancer to thrive and survive under hypovascular, nutrient-poor and hypoxic microenvironments, but also confers chemoresistance, which contributes to the poor prognosis of PDAC. In this review, we systematically elucidate the mechanism of chemotherapy resistance and the relationship of metabolic programming features with resistance to anticancer drugs in PDAC. Targeting the critical enzymes and/or transporters involved in glucose, lipid, and amino acid metabolism may be a promising approach to overcome chemoresistance in PDAC. Consequently, regulating metabolism could be used as a strategy against PDAC and could improve the prognosis of PDAC.

Identification of Fucosylated SERPINA1 as a Novel Plasma Marker for Pancreatic Cancer Using Lectin Affinity Capture Coupled with iTRAQ-Based Quantitative Glycoproteomics

Pancreatic cancer (PC) is an aggressive cancer with a high mortality rate, necessitating the development of effective diagnostic, prognostic and predictive biomarkers for disease management. Aberrantly fucosylated proteins in PC are considered a valuable resource of clinically useful biomarkers. The main objective of the present study was to identify novel plasma glycobiomarkers of PC using the iTRAQ quantitative proteomics approach coupled with Aleuria aurantia lectin (AAL)-based glycopeptide enrichment and isotope-coded glycosylation site-specific tagging, with a view to analyzing the glycoproteome profiles of plasma samples from patients with non-metastatic and metastatic PC and gallstones (GS). As a result, 22 glycopeptides with significantly elevated levels in plasma samples of PC were identified. Fucosylated SERPINA1 (fuco-SERPINA1) was selected for further validation in 121 plasma samples (50 GS and 71 PC) using an AAL-based reverse lectin ELISA technique developed in-house. Our analyses revealed significantly higher plasma levels of fuco-SERPINA1 in PC than GS subjects (310.7 ng/mL v.s. 153.6 ng/mL, p = 0.0114). Elevated fuco-SERPINA1 levels were associated with higher TNM stage (p = 0.024) and poorer prognosis for overall survival (log-rank test, p = 0.0083). The increased plasma fuco-SERPINA1 levels support the utility of this protein as a novel prognosticator for PC.

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

Simple Summary

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

Abstract

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

Review of clinical and emerging biomarkers for early diagnosis and treatment management of pancreatic cancer: towards personalised medicine

Background:

Pancreatic cancer is the 12th most commonly diagnosed cancer and the 3rd leading cause of cancer mortality and accounts for approximately 2·7% of all newly diagnosed cancer cases and 6·4% of all cancer mortalities in Canada. It has a very poor survival rate mainly due to the difficulty of detecting the disease at an early stage. Consequently, in the advancement of disease management towards the concept of precision medicine that takes individual patient variabilities into account, several investigators have focused on the identification of effective clinical biomarkers with high specificity and sensitivity, capable of early diagnosis of symptomatic patients and early detection of the disease in asymptomatic individuals at high risk for developing pancreatic cancer.

Materials and methods:

We searched several databases from August to December 2020 for relevant studies published in English between 2000 and 2020 and reporting on biomarkers for the management of pancreatic cancer. In this narrative review paper, we describe 13 clinical and emerging biomarkers for pancreatic cancers used in screening for early detection and diagnosis, to identify patients’ risk for metastatic disease and subsequent relapse, to monitor patient response to specific treatment and to provide clinicians the possibility of prospectively identifying groups of patients who will benefit from a particular treatment.

Conclusions:

Current and emerging biomarkers for pancreatic cancer with high specificity and sensitivity has the potential to account for individual patient variabilities, for early detection of disease before the onset of metastasis to improve treatment outcome and patients’ survival, help screen high-risk populations, predict prognosis, provide accurate information of patient response to specific treatment and improve patients monitoring during treatment. Thus, the future holds promise for the use of effective clinical biomarkers or a panel of biomarkers for personalised patient-specific targeted medicine for pancreatic cancer.

Early Detection of Pancreatic Cancer in Type 2 Diabetes Mellitus Patients Based on 1H NMR Metabolomics

The association of pancreatic cancer with type 2 diabetes mellitus was investigated by ¹H NMR metabolomic analysis of blood plasma. Concentration data of 58 metabolites enabled discrimination of pancreatic cancer (PC) patients from healthy controls (HC) and long-term type 2 diabetes mellitus (T2DM) patients. A panel of eight metabolites was proposed and successfully tested for group discrimination. Furthermore, a prediction model for the identification of at-risk individuals for future development of pancreatic cancer was built and tested on recent-onset diabetes mellitus (RODM) patients. Six of 59 RODM samples were assessed as PC with an accuracy of more than 80%. The health condition of these individuals was re-examined, and in four cases, a correlation to the prediction was found. The current health condition can be retrospectively attributed to misdiagnosed pancreatogenic diabetes or to early-stage pancreatic cancer.

Overall survival of pancreatic ductal adenocarcinoma is doubled by Aldh7a1 deletion in the KPC mouse

Rationale: The activity of aldehyde dehydrogenase 7A1 (ALDH7A1), an enzyme that catalyzes the lipid peroxidation of fatty aldehydes was found to be upregulated in pancreatic ductal adenocarcinoma (PDAC). ALDH7A1 knockdown significantly reduced tumor formation in PDAC. We raised a question how ALDH7A1 contributes to cancer progression. Methods: To answer the question, the role of ALDH7A1 in energy metabolism was investigated by knocking down and knockdown gene in mouse model, because the role of ALDH7A1 has been reported as a catabolic enzyme catalyzing fatty aldehyde from lipid peroxidation to fatty acid. Oxygen consumption rate (OCR), ATP production, mitochondrial membrane potential, proliferation assay and immunoblotting were performed. In in vivo study, two human PDAC cell lines were used for pre-clinical xenograft model as well as spontaneous PDAC model of KPC mice was also employed for anti-cancer therapeutic effect. Results:ALDH7A1 knockdown significantly reduced tumor formation with reduction of OCR and ATP production, which was inversely correlated with increase of 4-hydroxynonenal. This implies that ALDH7A1 is critical to process fatty aldehydes from lipid peroxidation. Overall survival of PDAC is doubled by cross breeding of KPC (KrasG12D; Trp53R172H; Pdx1-Cre) and Aldh7a1-/- mice. Conclusion: Inhibitions of ALDH7A1 and oxidative phosphorylation using gossypol and phenformin resulted in a regression of tumor formation in xenograft mice model and KPC mice model.

Identification of Circ_001569 as a Potential Biomarker in the Diagnosis and Prognosis of Pancreatic Cancer

Emerging evidence has shown that circular RNAs (circRNAs) serve as a promising biomarker in different malignancies. Specifically, circ_001569 has been found to be upregulated in some types of human gastrointestinal cancer. In this study, we aimed to investigate clinical significances, diagnostic and prognostic values of circ_001569 in pancreatic cancer (PC), and identify its effects on the malignant behaviors of PC cells. The expression of circ_001569 was determined in 26 tissues samples and 97 plasma samples from PC patients by qRT-PCR. Relationship between circ_001569 expression and clinicopathological parameters was analyzed by Chi-square test. Diagnostic and prognostic values of circ_001569 were evaluated by ROC curves, Kaplan-Meier curves, and Cox regression analysis. The effects of circ_001569 on the proliferation, migration, invasion, and apoptosis of PC cells were assessed by MTT, wound healing, Transwell invasion assays, and flow cytometric analysis, respectively. Results showed that the expression of circ_001569 was upregulated in tissues and plasma of PC patients. High circ_001569 level was positively correlated with lymphatic metastasis, clinical stage, and venous invasion. Circ_001569 level was an independent prognostic indicator for overall survival rates of PC patients, and patients with high circ_001569 level had a poor prognosis. The AUC of circ_001569 was 0.716 (95% CI: 0.642-0.790) with a sensitivity and specificity of 62.76% and 74.29%, respectively. In vitro, circ_001569 silencing decreased cell proliferation, migration, and invasion, but promoted cell apoptosis of PC cells. Our data demonstrate that high circ_001569 level associates with tumor malignant behaviors, and may serve as a potential biomarker in the diagnosis and prognosis of PC.

The Emerging Role of Microbiota and Microbiome in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignant tumors due to the absence of biomarkers for early-stage detection and poor response to therapy. Since mounting evidence supports the role of microbiota composition in tumorigenesis and cancer treatment, the link between microbiome and PDAC has been described. In this review, we summarize the current knowledge regarding the impact of the gut and oral microbiome on the risk of PDAC development. Microenvironment-driven therapy and immune system interactions are also discussed. More importantly, we provide an overview of the clinical trials evaluating the microbiota role in the risk, prognosis, and treatment of patients suffering from PDAC and solid tumors. According to the research findings, immune tolerance might result from the microbiota-derived remodeling of pancreatic tumor microenvironment. Thus, microbiome profiling and targeting represent the potential trend to enhance antitumor immunity and improve the efficacy of PDAC treatment.

Transcriptome analysis identifies putative multi-gene signature distinguishing benign and malignant pancreatic head mass

Background

Most often, the patients with pancreatic diseases are presented with a mass in pancreatic head region and existing methods of diagnosis fail to confirm whether the head mass is malignant or benign. As subsequent management of the disease hugely depends on the correct diagnosis, we wanted to explore possible biomarkers which could distinguish benign and malignant pancreatic head masses.

Methods

In order to address that gap, we performed a case–control study to identify genome-wide differentially expressed coding and noncoding genes between pancreatic tissues collected from benign and malignant head masses. These genes were next shortlisted using stringent criteria followed by selection of top malignancy specific genes. They subsequently got validated by quantitative RT-PCR and also in other patient cohorts. Survival analysis and ROC analysis were also performed.

Results

We identified 55 coding and 13 noncoding genes specific for malignant pancreatic head masses. Further shortlisting and validation, however, resulted in 5 coding genes as part of malignancy specific multi-gene signature, which was validated in three independent patient cohorts of 145 normal and 153 PDAC patients. We also found that overexpression of these genes resulted in survival disadvantage in the patients and ROC analysis identified that combination of 5 coding genes had the AUROC of 0.94, making them potential biomarker.

Conclusions

Our study identified a multi-gene signature comprising of 5 coding genes (CDCA7, DLGAP5, FOXM1, TPX2 and OSBPL3) to distinguish malignant head masses from benign ones.

Aptamers: a novel targeted theranostic platform for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is an extremely challenging disease with a high mortality rate and a short overall survival time. The poor prognosis can be explained by aggressive tumor growth, late diagnosis, and therapy resistance. Consistent efforts have been made focusing on early tumor detection and novel drug development. Various strategies aim at increasing target specificity or local enrichment of chemotherapeutics as well as imaging agents in tumor tissue. Aptamers have the potential to provide early detection and permit anti-cancer therapy with significantly reduced side effects. These molecules are in-vitro selected single-stranded oligonucleotides that form stable three-dimensional structures. They are capable of binding to a variety of molecular targets with high affinity and specificity. Several properties such as high binding affinity, the in vitro chemical process of selection, a variety of chemical modifications of molecular platforms for diverse function, non-immunoreactivity, modification of bioavailability, and manipulation of pharmacokinetics make aptamers attractive targets compared to conventional cell-specific ligands. To explore the potential of aptamers for early diagnosis and targeted therapy of PDAC - as single agents and in combination with radiotherapy - we summarize the generation process of aptamers and their application as biosensors, biomarker detection tools, targeted imaging tracers, and drug-delivery carriers. We are furthermore discussing the current implementation aptamers in clinical trials, their limitations and possible future utilization.

Current Strategies and Future Perspectives for Precision Medicine in Pancreatic Cancer

Current standard-of-care for patients with pancreatic ductal adenocarcinoma (PDAC) focusses on chemotherapeutic regimens and pancreatic cancer surgery. However, limited treatment options, late diagnosis in advanced tumor stages and the aggressive behavior of PDAC contribute to the high mortality of the disease. Consequently, there is an urgent need of precision medicine for pancreatic cancer patients. All over the world, numerous initiatives started in recent years to translate novel scientific discoveries into prospective clinical trials. One major approach pursues the stratification of PDAC patients according the tumor transcriptome to predict treatment response. Other strategies concentrate on genomic alterations and the identification of individualized targeted therapies. Further experimental studies are ongoing to detect novel biomarkers for cancer diagnosis, subtyping, treatment response prediction or clinical outcome. However, the challenge remains to transfer the knowledge into clinical practice. In this review, we summarize current literature and knowledge and highlight novel concepts of basic and clinical research uncovering suitable biomarkers and targeted therapies. Thus, we provide an overview of preclinical and clinical efforts of precision medicine in pancreatic cancer.

Proteostasis Dysregulation in Pancreatic Cancer

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

Effect of Perioperative CEA and CA24-2 on Prognosis of Early Resectable Pancreatic Ductal Adenocarcinoma

Patients with resectable pancreatic ductal adenocarcinoma (PDAC) show differential prognosis after radical resection. Currently, cancer grading and surgical criteria depend heavily on imaging and anatomical diagnosis. It's essential to set up a model with reliable prognostic factors during the perioperative period to assess prognosis in PDAC patients. In this study, 103 patients diagnosed with PDAC who underwent radical resection were recruited. The predictive value of preoperative carcinoembryonic antigen (CEA), postoperative CA24-2 and the combination of two for overall survival (OS) were evaluated. Both pre-CEA and post-CA24-2 were found to be independent prognostic factors for OS according to multivariate analyses. Kaplan-Meier analysis revealed that CEA and CA24-2 as well as the combination of two were correlated with poor OS. In addition, patients with both markers elevated have worse prognosis than patients with either pre-CEA or post-CA24-2 elevated. Thus, we concluded that the combination of CEA and CA24-2 can be used as a prognostic factor for stage I and II resectable PDAC patients.

KIF18B promotes the proliferation of pancreatic ductal adenocarcinoma via activating the expression of CDCA8

Pancreatic cancer is one of the malignant tumors with the worst prognosis, and the 5-year survival rate of this disease is less than 1%. About 90% of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), and targeting therapy has become a promising treatment for PDAC in recent years. To improve the survival rate, novel therapeutic targets for PDAC are still urgently needed. KIF18B was initially identified as a member of the kinesin family and involved in multiple cellular processes, such as separation of chromosomes in mitosis. Recently, it was found that KIF18B was involved in the growth and development of multiple cancers. However, the potential link between KIF18B and PDAC is still unclear. In this study, we demonstrated that KIF18B was highly expressed in human PDAC tissues, and related with the poor prognosis and clinical features, such as tumor size (*p = .013) and pTNM stage (*p = .025), of patients with PDAC. We further found that KIF18B knockdown blocked the cell proliferation of PDAC in vitro and in vivo, and the cell cycle was arrested caused by KIF18B depletion. Additionally, we also found that KIF18B bound to the promoter region of the cell division cycle associated 8 and thus activated its transcription. Taken together, this study explored the molecular mechanism underlying KIF18B promoting PDAC and provided a novel therapeutic target of this disease.

The metabolic time line of pancreatic cancer: Opportunities to improve early detection of adenocarcinoma

BACKGROUND

A reliable biomarker to detect pancreatic ductal adenocarcinoma (PDAC) continues to be elusive. With employing metabolomics we hypothesize that a broader analysis of systemic blood can differentiate different stages of PDAC.

METHODS

Patients undergoing pancreatic resection had plasma samples grouped by diagnosis and assayed with mass spectrometry. 10 per group [neuroendocrine (PNET), intraductal papillary mucinous neoplasm (IPMN), localized PDAC, locally advanced PDAC, and metastatic] were analyzed to assess if metabolites could delineation different stages of adenocarcinoma.

RESULTS

Of the 215 metabolites measured, four had a stronger correlation to disease burden than CA19-9. However, none of these metabolites differentiated stepwise progression in malignancy. Principal component analysis identified five metabolic components. Each cancer cohort was characterized by a unique combination of components, two components were predictors of PDCA stages.

CONCLUSIONS

Enhanced metabolomic analysis identified metabolic pathways that may assist in differentiating PDCA stages that do not occur in a linear stepwise progression.

Relationship between S100A4 protein expression and pre-operative serum CA19.9 levels in pancreatic carcinoma and its prognostic significance

BACKGROUND

Pancreatic carcinoma (PC) is one of the most lethal malignancies, and its poor prognosis is strongly associated with invasion and metastasis. CA19.9 is considered to be the most sensitive serum marker for PC in clinical practice; however, the detection of CA19.9 in PC has a certain false positive and false negative rate. The expression of the calcium-binding protein S100A4 has been reported to be associated with poor prognosis in various cancers. This study aimed to investigate the relationship between S100A4 and CA19.9 and its prognostic significance in PC.

METHODS

We performed immunohistochemical staining for S100A4 in formalin-fixed, paraffin-embedded blocks of 128 PC tissues. The levels of S100A4 expression and pre-operative serum CA19.9 were correlated with clinicopathological parameters. The possible correlation between S100A4 protein expression and pre-operative serum CA19.9 levels were evaluated using the chi-square test and Spearman correlation. Survival was assessed by Kaplan-Meier analysis together with a single variable or multivariate Cox analysis.

RESULTS

A significant positive correlation between S100A4 expression and pre-operative serum CA19.9 level was observed in PC tissues (ρ = 0.202, P = 0.022). The co-expression of both proteins correlated significantly with tumor differentiation (ρ = - 0.280, P = 0.001), TNM stage (ρ = - 0.389, P = 0.000), and lymph node metastasis (ρ = 0.254, P = 0.008). Upregulation of S100A4 was identified as a significant, independent predictor of poor overall survival (P = 0.000). Moreover, higher serum CA19.9 levels (≥ 35 U/mL) were also recognized as an independent predictor of inferior overall survival (P = 0.001). Additionally, upregulation of S100A4 and higher pre-operative serum CA19.9 levels (≥ 35 U/mL) in patients with PC contributed to a significant decrease in overall survival (P = 0.000).

CONCLUSIONS

The expression levels of S100A4 in PC tissues were positively correlated with pre-operative serum CA19.9 levels. S100A4 expression and pre-operative serum CA19.9 levels were significant, independent prognostic factors for the overall survival of patients with PC. S100A4 expression/pre-operative serum CA19.9 levels may prove useful as dual prognostic biomarkers for PC. Analysis of CA19.9 in combination with S100A4 can better predict the prognosis of PC.

Body site-dependent variations of microbiota in pancreatic cancer pathophysiology

Lack of specific symptoms and reliable biomarkers, along with aggressive nature and resistance to therapies makes pancreatic cancer (PC) one of the leading causes of death from cancer worldwide. The search for new diagnostic, prognostic, predictive, and therapeutic tools that could improve clinical outcomes of patients has led, in recent years, to the investigation of potential roles for the microbiota in the pathogenesis of this disease. The human microbiota encompasses trillions of microorganisms residing within several body tissues and organs, where they provide beneficial functions for host homeostasis and health. Derangements of the microbial ecology in different anatomic districts have been described in PC, as in many other diseases, both in patients and in animal models. In detail, infection from the gastric pathogen Helicobacter pylori and changes in composition and diversity of oral, intestinal, and pancreatic microbiota have been found to associate with PC. Future research should assess how to potentially exploit such differences in microbiota composition as diagnostic, prognostic, or predictive biomarkers, and as targets for therapeutic interventions, in the hope of improving the dismal prognosis of this insidious cancer.