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

Trefoil factor 1 suppresses stemness and enhances chemosensitivity of pancreatic cancer

BACKGROUND AND AIMS

Pancreatic cancer is one of the most lethal malignancies, partly due to resistance to conventional chemotherapy. The chemoresistance of malignant tumors is associated with epithelial-mesenchymal transition (EMT) and the stemness of cancer cells. The aim of this study is to investigate the availability and functional mechanisms of trefoil factor family 1 (TFF1), a tumor-suppressive protein in pancreatic carcinogenesis, to treat pancreatic cancer.

METHODS

To investigate the role of endogenous TFF1 in human and mice, specimens of human pancreatic cancer and genetically engineered mouse model of pancreatic cancer (KPC/TFF1KO; Pdx1-Cre/LSL-KRASG12D/LSL-p53R172H/TFF1-/-) were analyzed by immunohistochemistry (IHC). To explore the efficacy of extracellular administration of TFF1, recombinant and chemically synthesized TFF1 were administered to pancreatic cancer cell lines, a xenograft mouse model and a transgenic mouse model.

RESULTS

The deficiency of TFF1 was associated with increased EMT of cancer cells in mouse models of pancreatic cancer, KPC. The expression of TFF1 in cancer cells was associated with better survival rate of the patients who underwent chemotherapy, and loss of TFF1 deteriorated the benefit of gemcitabine in KPC mice. Extracellular administration of TFF1 inhibited gemcitabine-induced EMT, Wnt pathway activation and cancer stemness, eventually increased apoptosis of pancreatic cancer cells in vitro. In vivo, combined treatment of gemcitabine and subcutaneous administration of TFF1 arrested tumor growth in xenograft mouse model and resulted in the better survival of KPC mice by inhibiting EMT and cancer stemness.

CONCLUSION

These results indicate that TFF1 can contribute to establishing a novel strategy to treat pancreatic cancer patients by enhancing chemosensitivity.

The role of biomarkers in the early detection of pancreatic cancer

Pancreatic surveillance can detect early-stage pancreatic cancer and achieve long-term survival, but currently involves annual endoscopic ultrasound and MRI/MRCP, and is recommended only for individuals who meet familial/genetic risk criteria. To improve upon current approaches to pancreatic cancer early detection and to expand access, more accurate, inexpensive, and safe biomarkers are needed, but finding them has remained elusive. Newer approaches to early detection, such as using gene tests to personalize biomarker interpretation, and the increasing application of artificial intelligence approaches to integrate complex biomarker data, offer promise that clinically useful biomarkers for early pancreatic cancer detection are on the horizon.

The Potential of Fecal and Urinary Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: A Systematic Review

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer often diagnosed at advanced stages, highlighting the urgent need for early detection strategies. This systematic review explores the potential of fecal and urinary biomarkers for early PDAC detection. A comprehensive search identified eight relevant studies investigating various biomarkers, including proteins, metabolites, microbial profiles, DNA mutations, and non-coding RNAs. Promising findings suggest that urinary biomarkers related to metabolic alterations, inflammatory processes, fecal microbiome profiles, and fecal miRNAs hold diagnostic potential even at early stages of PDAC. Combining biomarkers into panels may enhance diagnostic accuracy. Challenges such as validation in larger cohorts, standardization of protocols, and regulatory approval must be addressed for clinical translation. Despite these hurdles, non-invasive urinary and fecal biomarkers represent a promising avenue for improving PDAC outcomes through early detection.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

Immunoassays: Analytical and Clinical Performance, Challenges, and Perspectives of SERS Detection in Comparison with Fluorescent Spectroscopic Detection

Immunoassays (IAs) with fluorescence-based detection are already well-established commercialized biosensing methods, such as enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay (LFIA). Immunoassays with surface-enhanced Raman spectroscopy (SERS) detection have received significant attention from the research community for at least two decades, but so far they still lack a wide clinical commercial application. This review, unlike any other review that we have seen, performs a three-dimensional performance comparison of SERS IAs vs. fluorescence IAs. First, we compared the limit of detection (LOD) as a key performance parameter for 30 fluorescence and 30 SERS-based immunoassays reported in the literature. We also compared the clinical performances of a smaller number of available reports for SERS vs. fluorescence immunoassays (FIAs). We found that the median and geometric average LODs are about 1.5-2 orders of magnitude lower for SERS-based immunoassays in comparison to fluorescence-based immunoassays. For instance, the median LOD for SERS IA is 4.3 × 10-13 M, whereas for FIA, it is 1.5 × 10-11 M. However, there is no significant difference in average relative standard deviation (RSD)-both are about 5-6%. The analysis of sensitivity, selectivity, and accuracy reported for a limited number of the published clinical studies with SERS IA and FIA demonstrates an advantage of SERS IA over FIA, at least in terms of the median value for all three of those parameters. We discussed common and specific challenges to the performances of both SERS IA and FIA, while proposing some solutions to mitigate those challenges for both techniques. These challenges include non-specific protein binding, non-specific interactions in the immunoassays, sometimes insufficient reproducibility, relatively long assay times, photobleaching, etc. Overall, this review may be useful for a large number of researchers who would like to use immunoassays, but particularly for those who would like to make improvements and move forward in both SERS-based IAs and fluorescence-based IAs.

Inhibition of Bromodomain Proteins Enhances Oncolytic HAdVC5 Replication and Efficacy in Pancreatic Ductal Adenocarcinoma (PDAC) Models

Pancreatic ductal adenocarcinoma (PDAC) is the most aggressive type of pancreatic cancer, which rapidly develops resistance to the current standard of care. Several oncolytic Human AdenoViruses (HAdVs) have been reported to re-sensitize drug-resistant cancer cells and in combination with chemotherapeutics attenuate solid tumour growth. Obstacles preventing greater clinical success are rapid hepatic elimination and limited viral replication and spread within the tumour microenvironment. We hypothesised that higher intratumoural levels of the virus could be achieved by altering cellular epigenetic regulation. Here we report on the screening of an enriched epigenetics small molecule library and validation of six compounds that increased viral gene expression and replication. The greatest effects were observed with three epigenetic inhibitors targeting bromodomain (BRD)-containing proteins. Specifically, BRD4 inhibitors enhanced the efficacy of Ad5 wild type, Ad∆∆, and Ad-3∆-A20T in 3-dimensional co-culture models of PDAC and in vivo xenografts. RNAseq analysis demonstrated that the inhibitors increased viral E1A expression, altered expression of cell cycle regulators and inflammatory factors, and attenuated expression levels of tumour cell oncogenes such as c-Myc and Myb. The data suggest that the tumour-selective Ad∆∆ and Ad-3∆-A20T combined with epigenetic inhibitors is a novel strategy for the treatment of PDAC by eliminating both cancer and associated stromal cells to pave the way for immune cell access even after systemic delivery of the virus.

Pancreatic Cancer and Detection Methods

The pancreas is a vital organ with exocrine and endocrine functions. Pancreatitis is an inflammation of the pancreas caused by alcohol consumption and gallstones. This condition can heighten the risk of pancreatic cancer (PC), a challenging disease with a high mortality rate. Genetic and epigenetic factors contribute significantly to PC development, along with other risk factors. Early detection is crucial for improving PC outcomes. Diagnostic methods, including imagining modalities and tissue biopsy, aid in the detection and analysis of PC. In contrast, liquid biopsy (LB) shows promise in early tumor detection by assessing biomarkers in bodily fluids. Understanding the function of the pancreas, associated diseases, risk factors, and available diagnostic methods is essential for effective management and early PC detection. The current clinical examination of PC is challenging due to its asymptomatic early stages and limitations of highly precise diagnostics. Screening is recommended for high-risk populations and individuals with potential benign tumors. Among various PC screening methods, the N-NOSE plus pancreas test stands out with its high AUC of 0.865. Compared to other commercial products, the N-NOSE plus pancreas test offers a cost-effective solution for early detection. However, additional diagnostic tests are required for confirmation. Further research, validation, and the development of non-invasive screening methods and standardized scoring systems are crucial to enhance PC detection and improve patient outcomes. This review outlines the context of pancreatic cancer and the challenges for early detection.

Evaluating Metabolite-Based Biomarkers for Early Diagnosis of Pancreatic Cancer: A Systematic Review

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers, with five-year survival rates around 10%. The only curative option remains complete surgical resection, but due to the delay in diagnosis, less than 20% of patients are eligible for surgery. Therefore, discovering diagnostic biomarkers for early detection is crucial for improving clinical outcomes. Metabolomics has become a powerful technology for biomarker discovery, and several metabolomic-based panels have been proposed for PDAC diagnosis, but these advances have not yet been translated into the clinic. Therefore, this review focused on summarizing metabolites identified for the early diagnosis of PDAC in the last five years. Bibliographic searches were performed in the PubMed, Scopus and WOS databases, using the terms "Biomarkers, Tumor", "Pancreatic Neoplasms", "Early Diagnosis", "Metabolomics" and "Lipidome" (January 2018-March 2023), and resulted in the selection of fourteen original studies that compared PDAC patients with subjects with other pancreatic diseases. These investigations showed amino acid and lipid metabolic pathways as the most commonly altered, reflecting their potential for biomarker research. Furthermore, other relevant metabolites such as glucose and lactate were detected in the pancreas tissue and body fluids from PDAC patients. Our results suggest that the use of metabolomics remains a robust approach to improve the early diagnosis of PDAC. However, these studies showed heterogeneity with respect to the metabolomics techniques used and further studies will be needed to validate the clinical utility of these biomarkers.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer (PanCa) presents a major concern and health burden. The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics; however, they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting. Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures. The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians. Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages. In this review, we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Automated classification of urine biomarkers to diagnose pancreatic cancer using 1-D convolutional neural networks

BACKGROUND

Early diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is the main key to surviving cancer patients. Urine proteomic biomarkers which are creatinine, LYVE1, REG1B, and TFF1 present a promising non-invasive and inexpensive diagnostic method of the PDAC. Recent utilization of both microfluidics technology and artificial intelligence techniques enables accurate detection and analysis of these biomarkers. This paper proposes a new deep-learning model to identify urine biomarkers for the automated diagnosis of pancreatic cancers. The proposed model is composed of one-dimensional convolutional neural networks (1D-CNNs) and long short-term memory (LSTM). It can categorize patients into healthy pancreas, benign hepatobiliary disease, and PDAC cases automatically.

RESULTS

Experiments and evaluations have been successfully done on a public dataset of 590 urine samples of three classes, which are 183 healthy pancreas samples, 208 benign hepatobiliary disease samples, and 199 PDAC samples. The results demonstrated that our proposed 1-D CNN + LSTM model achieved the best accuracy score of 97% and the area under curve (AUC) of 98% versus the state-of-the-art models to diagnose pancreatic cancers using urine biomarkers.

CONCLUSION

A new efficient 1D CNN-LSTM model has been successfully developed for early PDAC diagnosis using four proteomic urine biomarkers of creatinine, LYVE1, REG1B, and TFF1. This developed model showed superior performance on other machine learning classifiers in previous studies. The main prospect of this study is the laboratory realization of our proposed deep classifier on urinary biomarker panels for assisting diagnostic procedures of pancreatic cancer patients.

Pancreatic Cancer Biomarkers: Oncogenic Mutations, Tissue and Liquid Biopsies, and Radiomics-A Review

Pancreatic cancer is one of the most fatal malignancies, as approximately 80% of patients are at advanced stages by the time of diagnosis. The main reason for the poor overall survival is late diagnosis that is partially due to the lack of tools for early-stage detection. In addition, there are several challenges in evaluating response to treatment and predicting prognosis. In this article, we do a review of the most common pancreatic cancer biomarkers with emphasis in new and promising approaches. Liquid biopsies seem to have important clinical applications in early detection, screening, prognosis, and longitudinal monitoring of on-treatment patients. Together with biomarkers in imaging, can represent valuable alternative non-invasive tools in order to achieve a more effective management of pancreatic cancer patients.

Urinary Exosomes: A Promising Biomarker for Disease Diagnosis

Exosomes are nanoscale vesicles derived from endocytosis, formed by fusion of multivesicular bodies with membranes and secreted into the extracellular matrix or body fluids. Many studies have shown that exosomes can be present in a variety of biological fluids, such as plasma, urine, saliva, amniotic fluid, ascites, and sweat, and most types of cells can secrete exosomes. Exosomes play an important role in many aspects of human development, including immunity, cardiovascular diseases, neurodegenerative diseases, and neoplasia. Urine can be an alternative to blood or tissue samples as a potential source of disease biomarkers because of its simple, noninvasive, sufficient, and stable characteristics. Therefore, urinary exosomes have valuable potential for early screening, monitoring disease progression, prognosis, and treatment. The method for isolating urinary exosomes has been perfected, and exosome proteomics is widely used. Therefore, we review the potential use of urinary exosomes for disease diagnosis and summarize the related literature.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Urine biomarkers enable pancreatic cancer detection up to 2 years before diagnosis

The poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly attributed to late diagnosis. We assessed the predictive performance of our previously reported urine biomarker panel for earlier detection of PDAC (LYVE1, REG1B and TFF1) in prediagnostic samples, alone and in combination with plasma CA19-9. This nested case-control study included 99 PDAC cases with urine samples prospectively collected up to 5 years prior to PDAC diagnosis and 198 matched controls. The samples were obtained from the Shanghai Women's Health Study (SWHS), the Shanghai Men's Health Studies (SMHS) and the Southern Community Cohort Study (SCCS). The urine biomarkers were measured by ELISA. Plasma CA19-9 was quantified by Luminex. Multiple logistic regression and Wilcoxon rank-sum and Mann-Whitney test were used for analysis. The internal validation approach was applied and the validated AUC estimators are reported on. The algorithm of urinary protein panel, urine creatinine and age named PancRISK, displayed similar AUC as CA19-9 up to 1 year before PDAC diagnosis (AUC = 0.79); however, the combination enhanced the AUCs to 0.89, and showed good discriminative ability (AUC = 0.77) up to 2 years. The combination showed sensitivity (SN) of 72% at 90% specificity (SP), and SP of 59% at 90% SN up to 1 year and 60% SN with 80% SP and 53% SP with 80% SN up to 2 years before PDAC diagnosis. Adding the clinical information on BMI value resulted in the overall improvement in performance of the PancRISK score. When combined with CA19-9, the urinary panel reached a workable model for detecting PDAC cases up to 2 years prior to diagnosis.

Early Diagnosis of Pancreatic Cancer: Clinical Premonitions, Timely Precursor Detection and Increased Curative-Intent Surgery

BACKGROUND

The overall poor prognosis in pancreatic cancer is related to late clinical detection. Early diagnosis remains a considerable challenge in pancreatic cancer. Unfortunately, the onset of clinical symptoms in patients usually indicate advanced disease or presence of metastasis.

ANALYSIS AND RESULTS

Currently, there are no designated diagnostic or screening tests for pancreatic cancer in clinical use. Thus, identifying risk groups, preclinical risk factors or surveillance strategies to facilitate early detection is a target for ongoing research. Hereditary genetic syndromes are a obvious, but small group at risk, and warrants close surveillance as suggested by society guidelines. Screening for pancreatic cancer in asymptomatic individuals is currently associated with the risk of false positive tests and, thus, risk of harms that outweigh benefits. The promise of cancer biomarkers and use of 'omics' technology (genomic, transcriptomics, metabolomics etc.) has yet to see a clinical breakthrough. Several proposed biomarker studies for early cancer detection lack external validation or, when externally validated, have shown considerably lower accuracy than in the original data. Biopsies or tissues are often taken at the time of diagnosis in research studies, hence invalidating the value of a time-dependent lag of the biomarker to detect a pre-clinical, asymptomatic yet operable cancer. New technologies will be essential for early diagnosis, with emerging data from image-based radiomics approaches, artificial intelligence and machine learning suggesting avenues for improved detection.

CONCLUSIONS

Early detection may come from analytics of various body fluids (eg 'liquid biopsies' from blood or urine). In this review we present some the technological platforms that are explored for their ability to detect pancreatic cancer, some of which may eventually change the prospects and outcomes of patients with pancreatic cancer.

Differentiating Ductal Adenocarcinoma of the Pancreas from Benign Conditions Using Routine Health Records: A Prospective Case-Control Study

The study aimed to develop a prediction model for differentiating suspected PDAC from benign conditions. We used a prospective cohort of patients with pancreatic disease (n = 762) enrolled at the Barts Pancreas Tissue Bank (2008-2021) and performed a case-control study examining the association of PDAC (n = 340) with predictor variables including demographics, comorbidities, lifestyle factors, presenting symptoms and commonly performed blood tests. Age (over 55), weight loss in hypertensive patients, recent symptoms of jaundice, high serum bilirubin, low serum creatinine, high serum alkaline phosphatase, low red blood cell count and low serum sodium were identified as the most important features. These predictors were then used for training several machine-learning-based risk-prediction models on 75% of the cohort. Models were assessed on the remaining 25%. A logistic regression-based model had the best overall performance in the validation cohort (area-under-the-curve = 0.90; Spiegelhalter's z = -1·82, p = 0.07). Setting a probability threshold of 0.15 guided by the maximum F2-score of 0.855, 96.8% sensitivity was reached in the full cohort, which could lead to earlier detection of 84.7% of the PDAC patients. The prediction model has the potential to be applied in primary, secondary and emergency care settings for the early distinction of suspected PDAC patients and expedited referral to specialist hepato-pancreatico-biliary services.

Microfluidics-Based Urine Biopsy for Cancer Diagnosis: Recent Advances and Future Trends

Urine biopsy, allowing for the detection, analysis and monitoring of numerous cancer-associated urinary biomarkers to provide insights into cancer occurrence, progression and metastasis, has emerged as an attractive liquid biopsy strategy with enormous advantages over traditional tissue biopsy, such as noninvasiveness, large sample volume, and simple sampling operation. Microfluidics enables precise manipulation of fluids in a tiny chip and exhibits outstanding performance in urine biopsy owing to its minimization, low cost, high integration, high throughput and low sample consumption. Herein, we review recent advances in microfluidic techniques employed in urine biopsy for cancer detection. After briefly summarizing the major urinary biomarkers used for cancer diagnosis, we provide an overview of the typical microfluidic techniques utilized to develop urine biopsy devices. Some prospects along with the major challenges to be addressed for the future of microfluidic-based urine biopsy are also discussed.

Early diagnosis of pancreatic cancer: What strategies to avoid a foretold catastrophe

While great strides in improving survival rates have been made for most cancers in recent years, pancreatic ductal adenocarcinoma (PDAC) remains one of the solid tumors with the worst prognosis. PDAC mortality often overlaps with incidence. Surgical resection is the only potentially curative treatment, but it can be performed in a very limited number of cases. In order to improve the prognosis of PDAC, there are ideally two possible ways: the discovery of new strategies or drugs that will make it possible to treat the tumor more successfully or an earlier diagnosis that will allow patients to be operated on at a less advanced stage. The aim of this review was to summarize all the possible strategies available today for the early diagnosis of PDAC and the paths that research needs to take to make this goal ever closer. All the most recent studies on risk factors and screening modalities, new laboratory tests including liquid biopsy, new imaging methods and possible applications of artificial intelligence and machine learning were reviewed and commented on. Unfortunately, in 2022 the results for this type of cancer still remain discouraging, while a catastrophic increase in cases is expected in the coming years. The article was also written with the aim of highlighting the urgency of devoting more attention and resources to this pathology in order to reach a solution that seems more and more unreachable every day.

Advances in biomarkers and techniques for pancreatic cancer diagnosis

Pancreatic cancer is the most lethal type of malignancy and is characterized by high invasiveness without severe symptoms. It is difficult to detect PC at an early stage because of the low diagnostic accuracy of existing routine methods, such as abdominal ultrasound, CT, MRI, and endoscopic ultrasound (EUS). Therefore, it is of value to develop new diagnostic techniques for early detection with high accuracy. In this review, we aim to highlight research progress on novel biomarkers, artificial intelligence, and nanomaterial applications on the diagnostic accuracy of pancreatic cancer.

Insights on Proteomics-Driven Body Fluid-Based Biomarkers of Cervical Cancer

Cervical cancer is one of the top malignancies in women around the globe, which still holds its place despite being preventable at early stages. Gynecological conditions, even maladies like cervical cancer, still experience scrutiny from society owing to prevalent taboo and invasive screening methods, especially in developing economies. Additionally, current diagnoses lack specificity and sensitivity, which prolong diagnosis until it is too late. Advances in omics-based technologies aid in discovering differential multi-omics profiles between healthy individuals and cancer patients, which could be utilized for the discovery of body fluid-based biomarkers. Body fluids are a promising potential alternative for early disease detection and counteracting the problems of invasiveness while also serving as a pool of potential biomarkers. In this review, we will provide details of the body fluids-based biomarkers that have been reported in cervical cancer. Here, we have presented our perspective on proteomics for global biomarker discovery by addressing several pertinent problems, including the challenges that are confronted in cervical cancer. Further, we also used bioinformatic methods to undertake a meta-analysis of significantly up-regulated biomolecular profiles in CVF from cervical cancer patients. Our analysis deciphered alterations in the biological pathways in CVF such as immune response, glycolytic processes, regulation of cell death, regulation of structural size, protein polymerization disease, and other pathways that can cumulatively contribute to cervical cancer malignancy. We believe, more extensive research on such biomarkers, will speed up the road to early identification and prevention of cervical cancer in the near future.

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

Detection of Early-Stage Pancreatic Ductal Adenocarcinoma From Blood Samples: Results of a Multiplex Biomarker Signature Validation Study

INTRODUCTION

The IMMray PanCan-d test combines an 8-plex biomarker signature with CA19-9 in a proprietary algorithm to detect pancreatic ductal adenocarcinoma (PDAC) in serum samples. This study aimed to validate the clinical performance of the IMMray PanCan-d test and to better understand test performance in Lewis-null (le/le) individuals who cannot express CA19-9.

METHODS

Serum samples from 586 individuals were analyzed with the IMMray PanCan-d biomarker signature and CA19-9 assay, including 167 PDAC samples, 203 individuals at high risk of familial/hereditary PDAC, and 216 healthy controls. Samples were collected at 11 sites in the United States and Europe. The study was performed by Immunovia, Inc (Marlborough, MA), and sample identity was blinded throughout the study. Test results were automatically generated using validated custom software with a locked algorithm and predefined decision value cutoffs for sample classification.

RESULTS

The IMMray PanCan-d test distinguished PDAC stages I and II (n = 56) vs high-risk individuals with 98% specificity and 85% sensitivity and distinguished PDAC stages I-IV vs high-risk individuals with 98% specificity and 87% sensitivity. We identified samples with a CA19-9 value of 2.5 U/mL or less as probable Lewis-null (le/le) individuals. Excluding these 55 samples from the analysis increased the IMMray PanCan-d test sensitivity to 92% for PDAC stages I-IV (n = 157) vs controls (n = 379) while maintaining specificity at 99%; test sensitivity for PDAC stages I and II increased from 85% to 89%.

DISCUSSION

These results demonstrate the IMMray PanCan-d blood test can detect PDAC with high specificity (99%) and sensitivity (92%).

Impact of Tumor-Derived DNA Testing in Peritoneal Lavage of Pancreatic Cancer Patients with and Without Occult Intra-Abdominal Metastases

BACKGROUND

The fractional abundance of tumor-derived DNA in body fluids depends on the metastatic sites and the degree of expansion. We aimed to assess the clinical significance of tumor-derived DNA testing in the peritoneal lavage of patients with pancreatic cancer.

METHODS

The prevalence and abundance of tumor-derived DNA was assessed in 204 subjects with ascites by peritoneal lavage (AS) and the evaluable paired plasma (PL) from 149 pancreatic cancer patients undergoing abdominal exploration. Genetic profiles were evaluated by next-generation sequencing, and prognostic impact was assessed using Cox proportional hazard models.

RESULTS

Of 204 subjects, AS samples from patients with peritoneal dissemination (PER+) and positive cytology (CY+) showed significantly higher prevalence and abundance of tumor-derived DNA than those with negative counterparts. Tumor-derived DNA prevalence and abundance in AS were more likely to be higher than in paired PL in a subgroup of patients with PER+ and CY+, respectively. Next-generation sequencing revealed concordant or discrepant mutational patterns between the AS and PL samples. Multivariate analysis showed that both tumor-derived DNA in AS (hazard ratio [HR] 3.940, p = 0.009) and PL (HR 2.936, p = 0.026) were independently associated with poor survival in treatment-naïve patients. In patients who underwent resection, tumor-derived DNA positivity in the AS was more predictive of early recurrence than in PL.

CONCLUSIONS

Tumor-derived DNA in AS can serve as characterizing the genetic profiles of tumor cells attributable to the development of PER+ and predicting the minimal residual disease and early recurrence in patients with pancreatic cancer.

Towards an updated view on the clinical management of pancreatic adenocarcinoma: Current and future perspectives

Pancreatic cancer has a dire prognosis and will represent the second leading cause of cancer death in the next 10 years. The multifactorial approach represents one of the main issues in controlling the extension of this neoplasm. In recent years, the characteristics of the tumor microenvironment, metastasis mechanisms and the relationship between immune system and neoplastic cells have been described, which has made it possible to understand the pathophysiology of pancreatic adenocarcinoma. Currently, there is a failure to provide an effective preventive method or early detection, so patients present with an advanced stage at the time of diagnosis. Despite numerous efforts, little progress has been made in clinical outcome and in improving survival in long term. Therefore, in the recent years, diverse diagnostic tests, treatments and possible approaches have been developed in the fields of radiotherapy, chemotherapy and surgery to find a combination of them that improves life expectancy in patients diagnosed with pancreatic cancer. At the moment, numerous clinical trials are being conducted to evaluate preventive diagnostic procedures such as serological markers or perfecting available imaging tests. On the other hand, implementation of immunotherapy is being studied in a neoplasm that has lagged in the application of this procedure since present possible treatments do not substantially improve quality of life. Therefore, the purpose of our study is to summarize the main progresses that have been made in the diagnosis, treatment and screening of this disease, explaining the limitations that have been observed and analyzing future prospects in the management of this illness.

Application of Mass Spectrometry in Pancreatic Cancer Translational Research

Pancreatic cancer (PC) is one of the most common malignant tumors in the digestive tract worldwide, with increased morbidity and mortality. In recent years, with the development of surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, and the change of the medical thinking model, remarkable progress has been made in researching comprehensive diagnosis and treatment of PC. However, the present situation of diagnostic and treatment of PC is still unsatisfactory. There is an urgent need for academia to fully integrate the basic research and clinical data from PC to form a research model conducive to clinical translation and promote the proper treatment of PC. This paper summarized the translation progress of mass spectrometry (MS) in the pathogenesis, diagnosis, prognosis, and PC treatment to promote the basic research results of PC into clinical diagnosis and treatment.

Ultrasound-Based Method for the Identification of Novel MicroRNA Biomarkers in Prostate Cancer

The detection of circulating microRNA (miRNA)-based biomarkers represents an innovative, non-invasive method for the early detection of cancer. However, the low concentration of miRNAs released in body fluids and the difficult identification of the tumor site have limited their clinical use as effective cancer biomarkers. To evaluate if ultrasound treatment could amplify the release of extracellular cancer biomarkers, we treated a panel of prostate cancer (PCa) cell lines with an ultrasound-based prototype and profiled the release of miRNAs in the extracellular space, with the aim of identifying novel miRNA-based biomarkers that could be used for PCa diagnosis and the monitoring of tumor evolution. We provide evidence that US-mediated sonoporation amplifies the release of miRNAs from both androgen-dependent (AD) and -independent (AI) PCa cells. We identified four PCa-related miRNAs, whose levels in LNCaP and DU145 supernatants were significantly increased following ultrasound treatment: mir-629-5p, mir-374-5p, mir-194-5p, and let-7d-5p. We further analyzed a publicly available dataset of PCa, showing that the serum expression of these novel miRNAs was upregulated in PCa patients compared to controls, thus confirming their clinical relevance. Our findings highlight the potential of using ultrasound to identify novel cell-free miRNAs released from cancer cells, with the aim of developing new biomarkers with diagnostic and predictive value.

A Serum Marker for Early Pancreatic Cancer with a Possible Link to Diabetes

BACKGROUND

Pancreatic cancer (PC) has a grim prognosis, and an early diagnostic biomarker has been highly desired. The molecular link between diabetes and PC has not been well-established.

METHODS

Bioinformatics screening was performed for a serum PC marker. Experiments in cell lines (5 PC and 1 normal cell lines), mouse models, and human tissue staining (37 PC and 10 normal cases) were performed to test asprosin production from PC. Asprosin's diagnostic performance was tested with serums from multi-center cohorts (347 PC, 209 normal, and 55 additional diabetic subjects) and evaluated according to PC status, stages, and diabetic status, which was compared with that of CA19-9.

RESULTS

Asprosin, a diabetes-related hormone, was found from the bioinformatics screening, and its production from PC was confirmed. Serum asprosin levels from multi-center cohorts yielded an age-adjusted diagnostic AUC of 0.987 (95% confidence interval [CI] = 0.961 to 0.997), superior to that of CA19-9 (AUC = 0.876, 95% CI = 0.847 to 0.905), and a cut-off of 7.18 ng/mL, at which the validation set exhibited a sensitivity of 0.957 and a specificity of 0.924. Importantly, the performance was maintained in early-stage and non-metastatic PC, consistent with the tissue staining. A slightly lower performance against additional diabetic patients (n = 55) was restored by combining asprosin and CA19-9 (AUC = 0.985, 95% CI = 0.975 to 0.995).

CONCLUSION

Asprosin is presented as an early-stage PC serum marker that may provide clues for PC-induced diabetes. Larger prospective clinical studies are warranted to solidify its utility.

Pancreatic cancer in 2021: What you need to know to win

Pancreatic cancer is one of the solid tumors with the worst prognosis. Five-year survival rate is less than 10%. Surgical resection is the only potentially curative treatment, but the tumor is often diagnosed at an advanced stage of the disease and surgery could be performed in a very limited number of patients. Moreover, surgery is still associated with high post-operative morbidity, while other therapies still offer very disappointing results. This article reviews every aspect of pancreatic cancer, focusing on the elements that can improve prognosis. It was written with the aim of describing everything you need to know in 2021 in order to face this difficult challenge.

Early detection of pancreatic cancer: current state and future opportunities

PURPOSE OF REVIEW

Pancreatic ductal adenocarcinoma (PDAC) is third leading cause of cancer death in the United States, a lethal disease with no screening strategy. Although diagnosis at an early stage is associated with improved survival, clinical detection of PDAC is typically at an advanced symptomatic stage when best in class therapies have limited impact on survival.

RECENT FINDINGS

In recent years this status quo has been challenged by the identification of novel risk factors, molecular markers of early-stage disease and innovations in pancreatic imaging. There is now expert consensus that screening may be pursued in a cohort of individuals with increased likelihood of developing PDAC based on genetic and familial risk.

SUMMARY

The current review summarizes the known risk factors of PDAC, current knowledge and recent observations pertinent to early detection of PDAC in these risk groups and outlines future approaches that will potentially advance the field.

Distinguishing diabetes secondary to pancreatic diseases from type 2 diabetes mellitus

PURPOSE OF REVIEW

Diabetes secondary to pancreatic diseases (i.e., acute pancreatitis, chronic pancreatitis, and pancreatic cancer) is increasingly studied, but remains challenging to distinguish from type 2 diabetes (T2DM). We review the clinical significance and potential biomarkers that may help differentiate these types of diabetes.

RECENT FINDINGS

Recent studies have identified several complications (including nonvascular) that occur more frequently in patients with diabetes secondary to acute and chronic pancreatitis than T2DM, and biomarkers to differentiate these types of diabetes. There have been advances that may enable the enrichment of a population of adults with new onset diabetes to potentially screen for occult pancreatic cancer, but efforts are needed to identify and validate promising diagnostic biomarkers.

SUMMARY

High-quality studies are needed to more precisely understand the risk factors and natural course of diabetes secondary to pancreatic diseases. Mechanistic and interventional studies are awaited to provide insights that will distinguish diabetes secondary to pancreatic diseases and refine the management of hyperglycemia in this patient population.

Early screening and diagnosis strategies of pancreatic cancer: a comprehensive review

Pancreatic cancer is a highly malignant digestive system tumor with a poor prognosis. Most pancreatic cancer patients are diagnosed at an advanced stage or even metastasis due to its highly aggressive characteristics and lack of typical early symptoms. Thus, an early diagnosis of pancreatic cancer is crucial for improving its prognosis. Currently, screening is often applied in high‐risk individuals to achieve the early diagnosis of pancreatic cancer. Fully understanding the risk factors of pancreatic cancer and pathogenesis could help us identify the high‐risk population and achieve early diagnosis and timely treatment of pancreatic cancer. Notably, accumulating studies have been undertaken to improve the detection rate of different imaging methods and the diagnostic accuracy of endoscopic ultrasound‐guided fine‐needle aspiration (EUS‐FNA) which is the golden standard for pancreatic cancer diagnosis. In addition, there are currently no biomarkers with sufficient sensitivity and specificity for the diagnosis of pancreatic cancer to be applied in the clinic. As the only serum biomarker approved by the United States Food and Drug Administration, carbohydrate antigen 19‐9 (CA19‐9) is not recommended to be used in the early screening of pancreatic cancer because of its limited specificity. Recently, increasing numbers of studies focused on the discovering of novel serum biomarkers and exploring their combination with CA19‐9 in the detection of pancreatic cancer. Besides, the application of liquid biopsy involving circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), microRNAs (miRNAs), and exosomes in blood and biomarkers in urine, and saliva in pancreatic cancer diagnosis are drawing more and more attention. Furthermore, many innovative technologies such as artificial intelligence, computer‐aided diagnosis system, metabolomics technology, ion mobility spectrometry (IMS) associated technologies, and novel nanomaterials have been tested for the early diagnosis of pancreatic cancer and have shown promising prospects. Hence, this review aims to summarize the recent progress in the development of early screening and diagnostic methods, including imaging, pathological examination, serological examination, liquid biopsy, as well as other potential diagnostic strategies for pancreatic cancer.

Biomarkers in the diagnosis of pancreatic cancer: Are we closer to finding the golden ticket?

Pancreatic cancer (PC) is a leading cause of cancer related mortality on a global scale. The disease itself is associated with a dismal prognosis, partly due to its silent nature resulting in patients presenting with advanced disease at the time of diagnosis. To combat this, there has been an explosion in the last decade of potential candidate biomarkers in the research setting in the hope that a diagnostic biomarker may provide a glimmer of hope in what is otherwise quite a substantial clinical dilemma. Currently, serum carbohydrate antigen 19-9 is utilized in the diagnostic work-up of patients diagnosed with PC however this biomarker lacks the sensitivity and specificity associated with a gold-standard marker. In the search for a biomarker that is both sensitive and specific for the diagnosis of PC, there has been a paradigm shift towards a focus on liquid biopsy and the use of diagnostic panels which has subsequently proved to have efficacy in the diagnosis of PC. Currently, promising developments in the field of early detection on PC using diagnostic biomarkers include the detection of microRNA (miRNA) in serum and circulating tumour cells. Both these modalities, although in their infancy and yet to be widely accepted into routine clinical practice, possess merit in the early detection of PC. We reviewed over 300 biomarkers with the aim to provide an in-depth summary of the current state-of-play regarding diagnostic biomarkers in PC (serum, urinary, salivary, faecal, pancreatic juice and biliary fluid).

Pentraxin 3 is a stromally-derived biomarker for detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC), characterized by dense desmoplastic stroma laid down by pancreatic stellate cells (PSC), has no reliable diagnostic biomarkers for timely detection. A multi-center cohort of PDAC patients and controls (chronic pancreatitis, intra-ductal papillary neoplasms, gallstones and otherwise healthy) donated serum in an ethically approved manner. Serum PTX3 above 4.34 ng/mL has a higher sensitivity (86%, 95% confidence interval (CI): 65-97%) and specificity (86%, 95% CI: 79-91%), positive predictive value (97%) and likelihood ratio (6.05), and is superior when compared to serum CA19-9 and CEA for detection of PDAC. In vitro and ex vivo analyses of PTX3, in human PDAC samples, PSCs, cell lines and transgenic mouse model for PDAC, suggest that PTX3 originates from stromal cells, mainly PSC. In activated PSC, PTX3 secretion could be downregulated by rendering PSC quiescent using all-trans-retinoic acid (ATRA). PTX3 organizes hyaluronan in conjunction with tumor necrosis factor-stimulated gene 6 (TSG-6) and facilitates stellate and cancer cell invasion. In SCALOP clinical trial (ISRCTN96169987) testing chemo-radiotherapy without stromal targeting, PTX3 had no prognostic or predictive role. However, in STARPAC clinical trial (NCT03307148), stromal modulation by ATRA even at first dose is accompanied with serum PTX3 response in patients who later go on to demonstrate disease control but not those in whom the disease progresses. PTX3 is a putative stromally-derived biomarker for PDAC which warrants further testing in prospective, larger, multi-center cohorts and within clinical trials targeting stroma.

Comprehensive Analysis of RNA Expression Correlations between Biofluids and Human Tissues

In recent years, biofluid has been considered a promising source of non-invasive biomarkers for health monitoring and disease diagnosis. However, the expression consistency between biofluid and human tissue, which is fundamental to RNA biomarker development, has not been fully evaluated. In this study, we collected expression profiles across 53 human tissues and five main biofluid types. Utilizing the above dataset, we uncovered a globally positive correlation pattern between various biofluids (including blood, urine, bile, saliva and stool) and human tissues. However, significantly varied biofluid-tissue similarity levels and tendencies were observed between mRNA and lncRNA. Moreover, a higher correlation was found between biofluid types and their functionally related and anatomically closer tissues. In particular, a highly specific correlation was discovered between urine and the prostate. The biological sex of the donor was also proved to be an important influencing factor in biofluid-tissue correlation. Moreover, genes enriched in basic biological processes were found to display low variability across biofluid types, while genes enriched in catabolism-associated pathways were identified as highly variable.

Early disease biomarkers can be found using animal models urine proteomics

INTRODUCTION

Early disease detection is a prerequisite for early intervention. Urine is not subjected to homeostatic control, and therefore, it accumulates very early changes associated with disease processes, some of which may be used as biomarkers. Animal models must be used to identify urinary changes associated with very early stages of diseases to avoid potential interfering factors and obtain urine samples at a sufficiently early time point before pathological or clinical manifestations occur.

AREAS COVERED

We reviewed recent (from 2009-2020) urine proteome studies using animal models of many diseases. We focused on early changes in urine proteome of animal models, particularly changes occurring prior to alterations in blood tests, light microscopy observations and clinical manifestations. Additional studies relevant to the topic were also extracted from the references of the cited papers. Changes in the urine proteome at different disease stages and the ability of the urine proteome to differentiate among different animal models are also discussed in this review.

EXPERT COMMENTARY

Urine proteomes of animal models may reflect early changes that occur even before changes in blood parameters, light microscopy observations and clinical manifestations, suggesting the potential use of urinary biomarkers for the very early detection of human diseases.

Can we screen for pancreatic cancer? Identifying a sub-population of patients at high risk of subsequent diagnosis using machine learning techniques applied to primary care data

BACKGROUND

Pancreatic cancer (PC) represents a substantial public health burden. Pancreatic cancer patients have very low survival due to the difficulty of identifying cancers early when the tumour is localised to the site of origin and treatable. Recent progress has been made in identifying biomarkers for PC in the blood and urine, but these cannot be used for population-based screening as this would be prohibitively expensive and potentially harmful.

METHODS

We conducted a case-control study using prospectively-collected electronic health records from primary care individually-linked to cancer registrations. Our cases were comprised of 1,139 patients, aged 15-99 years, diagnosed with pancreatic cancer between January 1, 2005 and June 30, 2009. Each case was age-, sex- and diagnosis time-matched to four non-pancreatic (cancer patient) controls. Disease and prescription codes for the 24 months prior to diagnosis were used to identify 57 individual symptoms. Using a machine learning approach, we trained a logistic regression model on 75% of the data to predict patients who later developed PC and tested the model's performance on the remaining 25%.

RESULTS

We were able to identify 41.3% of patients < = 60 years at 'high risk' of developing pancreatic cancer up to 20 months prior to diagnosis with 72.5% sensitivity, 59% specificity and, 66% AUC. 43.2% of patients >60 years were similarly identified at 17 months, with 65% sensitivity, 57% specificity and, 61% AUC. We estimate that combining our algorithm with currently available biomarker tests could result in 30 older and 400 younger patients per cancer being identified as 'potential patients', and the earlier diagnosis of around 60% of tumours.

CONCLUSION

After further work this approach could be applied in the primary care setting and has the potential to be used alongside a non-invasive biomarker test to increase earlier diagnosis. This would result in a greater number of patients surviving this devastating disease.

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.

Urinary malate dehydrogenase 2 is a new biomarker for early detection of non-small-cell lung cancer

Reliable and noninvasive biomarkers for the early diagnosis of non‐small‐cell lung cancer (NSCLC) are an unmet need. This study aimed to screen and validate potential urinary biomarkers for the early diagnosis of NSCLC. Using protein mass spectrometry, urinary MDH2 was found to be abundant both in patients with lung cancer and lung cancer model mice compared with controls. Urine samples obtained as retrospective and prospective cohorts including 1091 NSCLC patients and 736 healthy controls were measured using ELISA. Patients with stage I NSCLC had higher urinary MDH2 compared with healthy controls. The area under the receiver‐operating characteristic curve (AUC) for the urinary MDH2 was 0.7679 and 0.7234 in retrospective and prospective cohorts to distinguish stage I cases from controls. Urinary MDH2 levels correlated with gender and smoking history. MDH2 expression levels were elevated in lung cancer tissues. MDH2 knockdown using shRNA inhibited the proliferation of lung cancer cells. Our study demonstrated that urinary MDH2 concentration was higher in early‐stage NSCLC patients compared with that in controls and that MDH2 could serve as a potential biomarker for early detection of NSCLC.

Urinary Biomarkers in Tumors: An Overview

Recent reports suggest that urine is a useful noninvasive tool for the identification of urogenital tumors, including bladder, prostate, kidney, and other nonurological cancers. As a liquid biopsy, urine represents an important source for the improvement of new promising biomarkers, a suitable tool to identify indolent cancer and avoid overtreatment. Urine is enriched with DNAs, RNAs, proteins, circulating tumor cells, exosomes, and other small molecules which can be detected with several diagnostic methodologies.We provide an overview of the ongoing state of urinary biomarkers underlying both their potential utilities to improve cancer prognosis, diagnosis, and therapeutic strategy and their limitations.

An Integrated Data Analysis of mRNA, miRNA and Signaling Pathways in Pancreatic Cancer

Although many genes and miRNAs have been reported for various cancers, pancreatic cancer's specific genes or miRNAs have not been studied precisely yet. Therefore, we have analyzed the gene and miRNA expression profile of pancreatic cancer data in the gene expression omnibus (GEO) database. The microarray-derived miRNAs and mRNAs were annotated by gene ontology (GO) and signaling pathway analysis. We also recognized mRNAs that were targeted by miRNA through the mirDIP database. An integrated analysis of the microarray revealed that only 6 out of 43 common miRNAs had significant differences in their expression profiles between the tumor and normal groups (P value < 0.05 and |log Fold Changes (logFC)|> 1). The hsa-miR-210 had upregulation, whereas hsa-miR-375, hsa-miR-216a, hsa-miR-217, hsa-miR-216b and hsa-miR-634 had downregulation in pancreatic cancer (PC). The analysis results also revealed 109 common mRNAs by microarray and mirDIP 4.1 databases. Pathway analysis showed that amoebiasis, axon guidance, PI3K-Akt signaling pathway, absorption and focal adhesion, adherens junction, platelet activation, protein digestion, human papillomavirus infection, extracellular matrix (ECM) receptor interaction, and riboflavin metabolism played important roles in pancreatic cancer. GO analysis revealed the significant enrichment in the three terms of biological process, cellular component, and molecular function, which were identified as the most important processes associated strongly with pancreatic cancer. In conclusion, DTL, CDH11, COL5A1, ITGA2, KIF14, SMC4, VCAN, hsa-mir-210, hsa-mir-217, hsa-mir-216a, hsa-mir-216b, hsa-mir-375 and hsa-mir-634 can be reported as the novel diagnostic or even therapeutic markers for the future studies. Also, the hsa-mir-107 and hsa-mir-125a-5p with COL5A1, CDH11 and TGFBR1 genes can be introduced as major miRNA and genes on the miRNA-drug-mRNA network. The new regulatory network created in our study could give a deeper knowledge of the pancreatic cancer.

Somatic Mutation Profiling in the Liquid Biopsy and Clinical Analysis of Hereditary and Familial Pancreatic Cancer Cases Reveals KRAS Negativity and a Longer Overall Survival

Simple Summary

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis. KRAS mutations occur in up to 95% of cases and render the tumor resistant to many types of therapy. Therefore, these patients are treated with traditional cytotoxic agents, according to guidelines. The familial or hereditary form of the disease accounts for up to 10–15% of cases. We hypothesized that hereditary and Familial Pancreatic Cancer cases (H/FPC) have a distinct tumor specific mutation profile due to the presence of pathogenic germline mutations and we used circulating free DNA (cfDNA) in plasma to assess this hypothesis. H/FPC cases were mainly KRAS mutation negative and harbored tumor specific mutations that are potential treatment targets in the clinic. Thus, we conclude that cases with a hereditary or familial background can be treated with newer and more effective agents that may ultimately improve their overall survival.

Abstract

Pancreatic ductal adenocarcinoma (PDAC) presents many challenges in the clinic and there are many areas for improvement in diagnostics and patient management. The five-year survival rate is around 7.2% as the majority of patients present with advanced disease at diagnosis that is treatment resistant. Approximately 10–15% of PDAC cases have a hereditary basis or Familial Pancreatic Cancer (FPC). Here we demonstrate the use of circulating free DNA (cfDNA) in plasma as a prognostic biomarker in PDAC. The levels of cfDNA correlated with disease status, disease stage, and overall survival. Furthermore, we show for the first time via BEAMing that the majority of hereditary or familial PDAC cases (around 84%) are negative for a KRAS somatic mutation. In addition, KRAS mutation negative cases harbor somatic mutations in potentially druggable genes such as KIT, PDGFR, MET, BRAF, and PIK3CA that could be exploited in the clinic. Finally, familial or hereditary cases have a longer overall survival compared to sporadic cases (10.2 vs. 21.7 months, respectively). Currently, all patients are treated the same in the clinic with cytotoxic agents, although here we demonstrate that there are different subtypes of tumors at the genetic level that could pave the way to personalized treatment.

Plasma protein biomarkers for early detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, mainly due to late diagnosis at advanced tumor stages. In this study, we aimed to identify plasma protein biomarkers for early detection of PDAC. Totally, 135 PDAC patients (early PDAC, Stage I/II, n = 71; advanced PDAC, Stage III/IV, n = 64), 13 benign lesions/chronic pancreatitis patients and 72 healthy individuals, with corresponding plasma samples from a case-control study in Sweden were included. A proximity extension assay was used to detect 92 cancer-related proteins, and an enzyme-linked immunosorbent assay/electrochemiluminescence immunoassay was used to detect CA19-9. Predictive features were selected from these 93 candidate proteins and three covariates in the Swedish participants, and then validated in Spanish participants, including 37 early PDAC patients, 38 advanced PDAC patients, 19 chronic pancreatitis patients and 36 healthy controls. A panel of eight proteins discriminating early PDAC from healthy individuals was identified, and the cross-validated area under the curves (AUCs) were 0.85 (95% confidence interval, 95% CI, 0.78-0.91) and 0.81 (95% CI, 0.70-0.92) in the Swedish and Spanish participants, respectively. Another eight-protein panel was predictive for classifying advanced PDAC from healthy controls in two populations, with cross-validated AUCs of 0.89 (95% CI, 0.83-0.95) and 0.90 (95% CI, 0.83-0.98), respectively. In conclusion, eight protein biomarkers were identified and externally validated, potentially allowing early detection of PDAC patients if validated in additional prospective studies.

High ARHGEF2 (GEF-H1) Expression is Associated with Poor Prognosis Via Cell Cycle Regulation in Patients with Pancreatic Cancer

BACKGROUND

Pancreatic cancer has an extremely poor prognosis, even after curative resection. Treatment options for pancreatic cancer remain limited, therefore new therapeutic targets are urgently needed. We searched for genes predictive of poor prognosis in pancreatic cancer using a public database and validated the survival impact of the selected gene in a patient cohort.

METHODS

We used a public database to search for genes associated with early pancreatic cancer recurrence. As a validation cohort, 201 patients who underwent radical resection in our institution were enrolled. Expression of the target gene was evaluated using immunohistochemistry (IHC). We evaluated growth and invasiveness using small interfering RNAs, then performed pathway analysis using gene set enrichment analysis.

RESULTS

We extracted ARHGEF2 from GSE21501 as a gene with a high hazard ratio (HR) for early recurrence within 1 year. The high ARHGEF2 expression group had significantly poorer recurrence-free survival (RFS) and poorer overall survival (OS) than the low ARHGEF2 expression group. Multivariate analysis demonstrated that high ARHGEF2 expression was an independent poor prognostic factor for RFS (HR 1.92) and OS (HR 1.63). In vitro, ARHGEF2 suppression resulted in reduced cell growth and invasiveness. Bioinformatic analysis revealed that ARHGEF2 expression was associated with MYC, G2M, E2F, and CDC25A expression, suggesting that c-Myc and cell cycle genes are associated with high ARHGEF2 expression. IHC revealed a positive correlation between ARHGEF2 and c-Myc expression.

CONCLUSIONS

High ARHGEF2 expression is associated with cell cycle progression, and predicts early recurrence and poor survival in patients with pancreatic cancer.

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

BACKGROUND

Pancreatic 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 FINDINGS

Clinical 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.

CONCLUSIONS

We 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.

Advances on diagnostic biomarkers of pancreatic ductal adenocarcinoma: A systems biology perspective

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy that is usually diagnosed at an advanced stage when curative surgery is no longer an option. Robust diagnostic biomarkers with high sensitivity and specificity for early detection are urgently needed. Systems biology provides a powerful tool for understanding diseases and solving challenging biological problems, allowing biomarkers to be identified and quantified with increasing accuracy, sensitivity, and comprehensiveness. Here, we present a comprehensive overview of efforts to identify biomarkers of PDAC using genomics, transcriptomics, proteomics, metabonomics, and bioinformatics. Systems biology perspective provides a crucial “network” to integrate multi-omics approaches to biomarker identification, shedding additional light on early PDAC detection.

Early Diagnosis of Pancreatic Cancer: The Key for Survival

Pancreatic cancer (PC) is one of the most aggressive forms of cancer. Negative prognosis is mainly due to the late diagnosis in advanced stages, when the disease is already therapeutically overcome. Studies in recent years have focused on identifying biomarkers that could play a role in early diagnosis, leading to the improvement of morbidity and mortality. Currently, the only biomarker widely used in the diagnosis of PC is carbohydrate antigen 19-9 (CA19.9), which has, however, more of a prognostic role in the follow-up of postoperative recurrence than a diagnostic role. Other biomarkers, recently identified as the methylation status of ADAMTS1 (A disintegrin and metalloproteinase with thrombospondin motifs 1) and BNC1 (zinc finger protein basonuclin-1) in cell-free deoxyribonucleic acid (DNA), may play a role in the early detection of PC. This review focuses on the diagnosis of PC in its early stages.

Review: Detection and quantification of proteins in human urine

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

•

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

•

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

•

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

•

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