Diagnostic accuracy and added value of blood-based protein biomarkers for pancreatic cancer: A meta-analysis of aggregate and individual participant data

Stroma gene signature predicts responsiveness to chemotherapy in pancreatic ductal adenocarcinoma patient-derived xenograft models

Despite many efforts to understand the molecular mechanisms of pancreatic ductal adenocarcinoma (PDAC) treatment resistance, there is still no reliable method for selecting patients who could benefit from standard pharmacological treatment. Here, four PDAC patient-derived xenografts (PDAC-PDXs) with different responses to gemcitabine plus nab-paclitaxel (nanoparticle albumin-bound paclitaxel) were studied to dissect the contribution of both tumor and host microenvironment to treatment response. PDAC-PDXs transplanted into the pancreas of immunodeficient mice retained the main genetic and histopathological characteristics of the original human tumors, including invasiveness and desmoplastic reaction. Response to chemotherapy was associated with a specific 294 stroma gene signature and was not due to the intrinsic responsiveness of tumor cells or differences in drug delivery. Human dataset analysis validated the expression of the 294 stroma gene signature in PDAC clinical samples, confirming PDAC-PDXs as a useful tool to study the biology of tumor-host interactions and to test drug efficacy. In summary, we identified a stroma gene signature that differentiates PDAC-PDXs that are responsive to gemcitabine plus Nab-paclitaxel treatment from those that are not, confirming the active role of the tumor microenvironment in the drug response.

Surgery for Locally Advanced Pancreatic Cancer Following Induction Chemotherapy: A Single-Center Experience

BACKGROUND

The use of surgery in patients with locally advanced pancreatic cancer (LAPC) following induction chemotherapy is increasing. However, most series do not report on the total cohort of patients undergoing surgical exploration; therefore, this single-center study investigates outcomes among all consecutive patients with LAPC who underwent surgical exploration.

METHODS

We conducted a retrospective, single-center analysis including all consecutive patients with LAPC (Dutch Pancreatic Cancer Group criteria) who underwent surgical exploration with curative intent (January 2014-June 2023) after induction therapy. Primary outcomes were resection rate and overall survival (OS) from the time of diagnosis.

RESULTS

Overall, 127 patients underwent surgical exploration for LAPC, whereby 100 patients (78.7%) underwent resection and 27 patients (21.3%) underwent a non-therapeutic laparotomy due to the extent of vascular involvement (n = 11, 8.7%) or occult metastases (n = 16, 12.6%). The overall in-hospital/30-day mortality rate was 0.8% and major morbidity was 31.3% (in patients after resection: 1.0% and 33.3%, respectively). The overall 90-day mortality rate was 5.5%, which included 3.1% mortality due to disease progression. Resection was associated with longer median OS {29 months (95% confidence interval [CI] 26-43) vs. 17 months (95% CI 11-26); p < 0.001} compared with patients undergoing non-therapeutic laparotomy, with corresponding 5-year OS rates of 28.4% and 7.7%. In Cox proportional hazard regression analysis, only pancreatic body/tail tumors independently predicted OS (hazard ratio 1.788 [95% CI 1.042-3.068]).

CONCLUSION

This single-center series found a resection rate of 78.7% in patients with LAPC selected for surgical exploration, with a low risk of mortality and morbidity in all explored patients and a 5-year OS rate after resection of 28.4%.

Identification of a serum proteomic biomarker panel using diagnosis specific ensemble learning and symptoms for early pancreatic cancer detection

BACKGROUND

The grim (<10% 5-year) survival rates for pancreatic ductal adenocarcinoma (PDAC) are attributed to its complex intrinsic biology and most often late-stage detection. The overlap of symptoms with benign gastrointestinal conditions in early stage further complicates timely detection. The suboptimal diagnostic performance of carbohydrate antigen (CA) 19-9 and elevation in benign hyperbilirubinaemia undermine its reliability, leaving a notable absence of accurate diagnostic biomarkers. Using a selected patient cohort with benign pancreatic and biliary tract conditions we aimed to develop a data analysis protocol leading to a biomarker signature capable of distinguishing patients with non-specific yet concerning clinical presentations, from those with PDAC.

METHODS

539 patient serum samples collected under the Accelerated Diagnosis of neuro Endocrine and Pancreatic TumourS (ADEPTS) study (benign disease controls and PDACs) and the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS, healthy controls) were screened using the Olink Oncology II panel, supplemented with five in-house markers. 16 specialized base-learner classifiers were stacked to select and enhance biomarker performances and robustness in blinded samples. Each base-learner was constructed through cross-validation and recursive feature elimination in a discovery set comprising approximately two thirds of the ADEPTS and UKCTOCS samples and contrasted specific diagnosis with PDAC.

RESULTS

The signature which was developed using diagnosis-specific ensemble learning demonstrated predictive capabilities outperforming CA19-9, the only biomarker currently accepted by the FDA and the National Comprehensive Cancer Network guidelines for pancreatic cancer, and other individual biomarkers and combinations in both discovery and held-out validation sets. An AUC of 0.98 (95% CI 0.98-0.99) and sensitivity of 0.99 (95% CI 0.98-1) at 90% specificity was achieved with the ensemble method, which was significantly larger than the AUC of 0.79 (95% CI 0.66-0.91) and sensitivity 0.67 (95% CI 0.50-0.83), also at 90% specificity, for CA19-9, in the discovery set (p = 0.0016 and p = 0.00050, respectively). During ensemble signature validation in the held-out set, an AUC of 0.95 (95% CI 0.91-0.99), sensitivity 0.86 (95% CI 0.68-1), was attained compared to an AUC of 0.80 (95% CI 0.66-0.93), sensitivity 0.65 (95% CI 0.48-0.56) at 90% specificity for CA19-9 alone (p = 0.0082 and p = 0.024, respectively). When validated only on the benign disease controls and PDACs collected from ADEPTS, the diagnostic-specific signature achieved an AUC of 0.96 (95% CI 0.92-0.99), sensitivity 0.82 (95% CI 0.64-0.95) at 90% specificity, which was still significantly higher than the performance for CA19-9 taken as a single predictor, AUC of 0.79 (95% CI 0.64-0.93) and sensitivity of 0.18 (95% CI 0.03-0.69) (p = 0.013 and p = 0.0055, respectively).

CONCLUSION

Our ensemble modelling technique outperformed CA19-9, individual biomarkers and indices developed with prevailing algorithms in distinguishing patients with non-specific but concerning symptoms from those with PDAC, with implications for improving its early detection in individuals at risk.

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.

Which is the best TACE agent for patients with different NLR hepatocellular carcinomas? A systematic review and network meta-analysis

Background

Transarterial chemoembolization (TACE) is a common treatment for hepatocellular carcinoma (HCC), but the best therapeutic agent for TACE treatment has not been determined. The neutrophil/lymphocyte ratio (NLR) is a systemic immune system marker; however, the ability of the NLR to predict the prognosis of patients with HCC is unknown, and no studies have been conducted to determine the most appropriate TACE regimen for HCC patients with different NLRs.

Methods

The PubMed, Embase, Web of Science, and CNKI databases were searched through May 28, 2023. Comparisons of overall survival (OS) among cohort studies with different NLRs and different TACE treatment regimens were performed with a random effects model.

Findings

Thirty-five studies involving 9210 patients were included in this meta-analysis. The results showed that Group 3-4 (NLR<2.5) patients had a significantly longer OS than Group 1-2 (NLR 2.5-5.0). Among the patients, Group 1-3 (NLR 2.0-5.0) patients had the best survival after treatment with adriamycin (lnHR (95 % CI = 0.48 [0.31, 0.75] and lnHR (95 % CI = 0.41 [0.19, 0.91]). Among the Group 4 patients (NLR<2.0), the best outcome was obtained with platinum + adriamycin (lnHR (95 % CI = 0.59 [0.45, 0.78]), followed by adriamycin. A subgroup analysis of TACE combined with other treatments showed that adriamycin combined with sorafenib was the most effective and superior to the other treatment agents.

Interpretation

The NLR can be used to predict the prognosis of HCC patients treated with TACE; the higher the NLR is, the worse the prognosis. Adriamycin may be the best therapeutic agent for HCC patients treated with TACE.

Prognostic nutritional index as a predictive marker for acute kidney injury in adult critical illness population: a systematic review and diagnostic test accuracy meta-analysis

BACKGROUND

The prognostic nutritional index (PNI), integrating nutrition and inflammation markers, has been increasingly recognized as a prognostic predictor in diverse patient cohorts. Recently, its effectiveness as a predictive marker for acute kidney injury (AKI) in various clinical settings has gained attention. This study aims to assess the predictive accuracy of the PNI for AKI in critically ill populations through systematic review and meta-analysis.

METHODS

A systematic review was conducted using the databases MEDLINE, EMBASE, PubMed, and China National Knowledge Infrastructure up to August 2023. The included trials reported the PNI assessment in adult population with critical illness and its predictive capacity for AKI. Data on study characteristics, subgroup covariates, and diagnostic performance of PNI, including sensitivity, specificity, and event rates, were extracted. A diagnostic test accuracy meta-analysis was performed. Subgroup analyses and meta-regression were utilized to investigate the sources of heterogeneity. The GRADE framework evaluated the confidence in the meta-analysis's evidence.

RESULTS

The analysis encompassed 16 studies with 17 separate cohorts, totaling 21,239 patients. The pooled sensitivity and specificity of PNI for AKI prediction were 0.67 (95% CI 0.58-0.74) and 0.74 (95% CI 0.67-0.80), respectively. The pooled positive likelihood ratio was 2.49 (95% CI 1.99-3.11; low certainty), and the negative likelihood ratio was 0.46 (95% CI 0.37-0.56; low certainty). The pooled diagnostic odds ratio was 5.54 (95% CI 3.80-8.07), with an area under curve of summary receiver operating characteristics of 0.76. Subgroup analysis showed that PNI's sensitivity was higher in medical populations than in surgical populations (0.72 vs. 0.55; p < 0.05) and in studies excluding patients with chronic kidney disease (CKD) than in those including them (0.75 vs. 0.56; p < 0.01). Overall, diagnostic performance was superior in the non-chronic kidney disease group.

CONCLUSION

Our study demonstrated that PNI has practical accuracy for predicting the development of AKI in critically ill populations, with superior diagnostic performance observed in medical and non-CKD populations. However, the diagnostic efficacy of the PNI has significant heterogeneity with different cutoff value, indicating the need for further research.

Identification of fibronectin type III domain containing 3B as a potential prognostic and therapeutic target for pancreatic cancer: a preliminary analysis

BACKGROUND

Fibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated.

METHODS

In this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan-Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored.

RESULTS

The study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan-Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells.

CONCLUSION

Despite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.

Clinical significance of tumor suppressor genes methylation in circulating tumor DNA of patients with pancreatic cancer

BACKGROUND

Circulating tumor DNA (ctDNA) has emerged as a potential diagnostic and prognostic biomarker in various tumors. However, the role of tumor suppressor genes (TSGs) methylation in ctDNA of patients with pancreatic cancer (PC) remains largely unclear.

METHODS

Patients with PC (n = 43), pancreatic benign diseases (n = 39), and healthy controls (n = 20) were enrolled in the study. Quantitative analysis of methylation pattern of five candidate TSGs including NPTX2, RASSF1A, EYA2, p16, and ppENK in ctDNA was performed by next generation sequencing (NGS). The diagnostic performances of these 5-TSGs methylation were assessed by the operating characteristic (ROC) curve and clinicopathological features correlation analysis. Meanwhile, the changes in methylation levels of these 5-TSGs on the 7th postoperative day were evaluated in 23 PC patients who underwent radical resection.

RESULTS

The methylation levels of RASSF1A, EYA2, ppENK and p16 genes in patients with PC were significantly higher than those in healthy controls. EYA2, p16 and ppENK genes showed significantly hypermethylation in PC than those in pancreatic benign diseases. NPTX2, RASSF1A, EYA2, p16 and ppENK genes showed significantly hypermethylation in pancreatic benign diseases than those in healthy controls (P < 0.05). The methylation levels of these 5 candidate TSGs were not correlated with the tumor size, nerve invasion, lymph node metastasis and TNM stage of PC. The AUC of these biomarkers for diagnosis of PC ranged from 0.65 to 0.96. The AUC values of these methylated genes and CpG sites for differentiating malignant and benign pancreatic diseases were ranging from 0.68 to 0.92. Combined the hypermethylated genes improved the detective ability of PC than single gene. The methylation levels of NPTX2, EYA2 and ppENK genes were significantly decreased after radical resection of PC.

CONCLUSION

Quantitative analysis of methylation pattern of NPTX2, RASSF1A, EYA2, p16 and ppENK in ctDNA by NGS could be a valuable non-invasive tool for detection and monitoring of PC.

Evaluations of the combined use of blood- and tissue-based protein biomarkers for pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a low 5-year survival rate. Biomarkers may be of value for the early diagnosis of pancreatic cancer. This study assessed blood- and tumour tissue-based biomarkers associated with pancreatic cancer.

METHODS

We studied 61 patients who underwent pancreatic resection. Of these 61 patients, 46 patients had PDAC, and 15 patients had inflammatory tumours. Blood and tumour tissue levels of VEGF, hypoxia-inducible factor 1α (HIF-1α) and glucose transporter 1 (GLUT1) were measured.

RESULTS

Blood concentrations of VEGF (p < 0.000001) and HIF-1α (p = 0.000002) were significantly higher in the PDAC group than in the inflammatory tumour group. Tumour tissue concentrations of VEGF (p < 0.000001), HIF-1α (p = 0.000005) and GLUT1 (0.000002) were also significantly higher in the PDAC group. Univariate analyses revealed that age, BMI, and blood levels of CA19-9, VEGF, and HIF-1α were potential predictors of PDAC. Potential predictors of PDAC in tumour tissue were VEGF, HIF-1α and GLUT1. Multivariate analyses found that VEGF was the most powerful independent predictor of PDAC in blood (OR = 1.016; 95% CI: 1.007-1.025; 0.001) and tumour tissue (OR = 1.02; 95% CI: 1.008-1.032, p = 0.001). The cut-off point for blood VEGF was 134.56 pg/ml, with a sensitivity of 97.8%, specificity of 86.7%, PPV of 95.7%, and NPV of 92.9%. The cut-off point for tissue tumour VEGF in PDAC was 208.59 pg/mg, with a sensitivity, specificity, PPV and NPV of 97.7%, 92.9%, 97.7%, and 92.9%, respectively.

CONCLUSIONS

There are significant differences in blood-based biomarkers for differentiating between PDAC and inflammatory tumours of the pancreas. VEGF was an independent predictor of PDAC independent of its addition to the routinely used tumour marker CA19-9 antigen.

A Comprehensive Review of the Potential Role of Liquid Biopsy as a Diagnostic, Prognostic, and Predictive Biomarker in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma is one of the most lethal malignant diseases, with a mortality rate being close to incidence. Due to its heterogeneity and plasticity, as well as the lack of distinct symptoms in the early phases, it is very often diagnosed at an advanced stage, resulting in poor prognosis. Traditional tissue biopsies remain the gold standard for making a diagnosis, but have an obvious disadvantage in their inapplicability for frequent sampling. Blood-based biopsies represent a non-invasive method which potentially offers easy and repeated sampling, leading to the early detection and real-time monitoring of the disease and hopefully an accurate prognosis. Given the urgent need for a reliable biomarker that can estimate a patient's condition and response to an assigned treatment, blood-based biopsies are emerging as a potential new tool for improving patients' survival and surveillance. In this article, we discuss the current advances and challenges in using liquid biopsies for pancreatic cancer, focusing on circulating tumour DNA (ctDNA), extracellular vesicles (EVs), and circulating tumour cells (CTCs), and compare the performance and reliability of different biomarkers and combinations of biomarkers.

Advances in the management of pancreatic cancer

Pancreatic cancer remains among the malignancies with the worst outcomes. Survival has been improving, but at a slower rate than other cancers. Multimodal treatment, including chemotherapy, surgical resection, and radiotherapy, has been under investigation for many years. Because of the anatomical characteristics of the pancreas, more emphasis on treatment selection has been placed on local extension into major vessels. Recently, the development of more effective treatment regimens has opened up new treatment strategies, but urgent research questions have also become apparent. This review outlines the current management of pancreatic cancer, and the recent advances in its treatment. The review discusses future treatment pathways aimed at integrating novel findings of translational and clinical research.

Thinking small to win big? A critical review on the potential application of extracellular vesicles for biomarker discovery and new therapeutic approaches in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is an extremely deadly form of cancer, with limited progress in 5-year survival rates despite significant research efforts. The main challenges in treating PDAC include difficulties in early detection, and resistance to current therapeutic approaches due to aggressive molecular and microenvironment features. These challenges emphasize the importance of identifying clinically validated biomarkers for early detection and clinical management. Extracellular vesicles (EVs), particularly exosomes, have emerged as crucial mediators of intercellular communication by transporting molecular cargo. Recent research has unveiled their role in initiation, metastasis, and chemoresistance of PDAC. Consequently, utilizing EVs in liquid biopsies holds promise for the identification of biomarkers for early detection, prognosis, and monitoring of drug efficacy. However, numerous limitations, including challenges in isolation and characterization of homogeneous EVs populations, as well as the absence of standardized protocols, can affect the reliability of studies involving EVs as biomarkers, underscoring the necessity for a prudent approach. EVs have also garnered considerable attention as a promising drug delivery system and novel therapy for tumors. The loading of biomolecules or chemical drugs into exosomes and their subsequent delivery to target cells can effectively impede tumor progression. Nevertheless, there are obstacles that must be overcome to ensure the accuracy and efficacy of therapies relying on EVs for the treatment of tumors. In this review, we examine both recent advancements and remaining obstacles, exploring the potential of utilizing EVs in biomarker discovery as well as for the development of drug delivery vehicles.

Managing complications of chronic pancreatitis: a guide for the gastroenterologist

INTRODUCTION

Chronic pancreatitis is a heterogeneous and complex syndrome that, in most cases, causes pain as a cardinal symptom and affects both the morphology and function of the pancreas, leading to several serious complications.

AREAS COVERED

The present review, based on a non-systematic PubMed search updated to June 2023, aims to present the current available evidence on the role of gastroenterologists in the diagnosis and treatment of both local and systemic complications by either endoscopic or medical treatments.

EXPERT OPINION

At diagnosis and during chronic pancreatitis follow-up, particular care is needed to consider not only the clinically manifest signs and symptoms of the disease, such as pain, jaundice, gastrointestinal obstruction, and pseudocysts, which require multidisciplinary discussion to establish the best treatment option (endoscopic or surgical), but also less evident systemic complications. Pancreatic exocrine and endocrine insufficiency, together with chronic inflammation, addiction, and dysbiosis, contribute to malnutrition, sarcopenia, and osteopathy. These complications, in turn, increase the risk of infection, thromboembolic events, and death. Patients with chronic pancreatitis also have an increased risk of psychiatric disorders and pancreatic cancer onset. Overall, patients with chronic pancreatitis should receive a holistic evaluation, considering all these aspects, possibly through multidisciplinary care in dedicated expert centers.

Prediction Model for Early-Stage Pancreatic Cancer Using Routinely Measured Blood Biomarkers

IMPORTANCE

Accurate risk prediction models using routinely measured biomarkers-eg, carbohydrate antigen 19-9 (CA19-9) and bilirubin serum levels-for pancreatic cancer could facilitate early detection of pancreatic cancer and prevent potentially unnecessary diagnostic tests for patients at low risk. An externally validated model using CA19-9 and bilirubin serum levels in a larger cohort of patients with pancreatic cancer or benign periampullary diseases is needed.

OBJECTIVE

To assess the discrimination, calibration, and clinical utility of a prediction model using readily available blood biomarkers (carbohydrate antigen 19-9 [CA19-9] and bilirubin) to distinguish early-stage pancreatic cancer from benign periampullary diseases.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study used data from 4 academic hospitals in Italy, the Netherlands, and the UK on adult patients with pancreatic cancer or benign periampullary disease treated from 2014 to 2022. Analyses were conducted from September 2022 to February 2023.

EXPOSURES

Serum levels of CA19-9 and bilirubin from samples collected at diagnosis and before start of any medical intervention.

MAIN OUTCOMES AND MEASURES

Discrimination (measured by the area under the curve [AUC]), calibration, and clinical utility of the prediction model and the biomarkers, separately.

RESULTS

The study sample comprised 249 patients in the development cohort (mean [SD] age at diagnosis, 67 [11] years; 112 [45%] female individuals), and 296 patients in the validation cohort (mean [SD] age at diagnosis, 68 [12] years; 157 [53%] female individuals). At external validation, the prediction model showed an AUC of 0.89 (95% CI, 0.84-0.93) for early-stage pancreatic cancer vs benign periampullary diseases, and outperformed CA19-9 (difference in AUC [ΔAUC], 0.10; 95% CI, 0.06-0.14; P < .001) and bilirubin (∆AUC, 0.07; 95% CI, 0.02-0.12; P = .004). In the subset of patients without elevated tumor marker levels (CA19-9 <37 U/mL), the model showed an AUC of 0.84 (95% CI, 0.77-0.92). At a risk threshold of 30%, decision curve analysis indicated that performing biopsies based on the prediction model was equivalent to reducing the biopsy procedure rate by 6% (95% CI, 1%-11%), without missing early-stage pancreatic cancer in patients.

CONCLUSIONS AND RELEVANCE

In this diagnostic study of patients with pancreatic cancer or benign periampullary diseases, an easily applicable risk score showed high accuracy for distinguishing early-stage pancreatic cancer from benign periampullary diseases. This model could be used to assess the added diagnostic and clinical value of novel biomarkers and prevent potentially unnecessary invasive diagnostic procedures for patients at low risk.

Pancreatic Cancer: Changing Epidemiology and New Approaches to Risk Assessment, Early Detection, and Prevention

Pancreatic cancer usually results in poor survival with limited options for treatment, as most affected individuals present with advanced disease. Early detection of preinvasive pancreatic neoplasia and identifying molecular therapeutic targets provide opportunities for extending survival. Although screening for pancreatic cancer is currently not recommended for the general population, emerging evidence indicates that pancreatic surveillance can improve outcomes for individuals in certain high-risk groups. Changes in the epidemiology of pancreatic cancer, experience from pancreatic surveillance, and discovery of novel biomarkers provide a roadmap for new strategies for pancreatic cancer risk assessment, early detection, and prevention.

Pancreatic Cancer in Chronic Pancreatitis: Pathogenesis and Diagnostic Approach

Chronic pancreatitis is one of the main risk factors for pancreatic cancer, but it is a rare event. Inflammation and oncogenes work hand in hand as key promoters of this disease. Tobacco is another co-factor. During alcoholic chronic pancreatitis, the cumulative risk of cancer is estimated at 4% after 15 to 20 years. This cumulative risk is higher in hereditary pancreatitis: 19 and 12% in the case of PRSS1 and SPINK1 mutations, respectively, at an age of 60 years. The diagnosis is difficult due to: (i) clinical symptoms of cancer shared with those of chronic pancreatitis; (ii) the parenchymal and ductal remodeling of chronic pancreatitis rendering imaging analysis difficult; and (iii) differential diagnoses, such as pseudo-tumorous chronic pancreatitis and paraduodenal pancreatitis. Nevertheless, the occurrence of cancer during chronic pancreatitis must be suspected in the case of back pain, weight loss, unbalanced diabetes, and jaundice, despite alcohol withdrawal. Imaging must be systematically reviewed. Endoscopic ultrasound-guided fine-needle biopsy can contribute by targeting suspicious tissue areas with the help of molecular biology (search for KRAS, TP53, CDKN2A, DPC4 mutations). Short-term follow-up of patients is necessary at the clinical and paraclinical levels to try to diagnose cancer at a surgically curable stage. Pancreatic surgery is sometimes necessary if there is any doubt.

Screening for pancreatic cancer has the potential to save lives, but is it practical?

INTRODUCTION

Most patients with pancreatic cancer present with advanced stage, incurable disease. However, patients with high-grade precancerous lesions and many patients with low-stage disease can be cured with surgery, suggesting that early detection has the potential to improve survival. While serum CA19.9 has been a long-standing biomarker used for pancreatic cancer disease monitoring, its low sensitivity and poor specificity have driven investigators to hunt for better diagnostic markers.

AREAS COVERED

This review will cover recent advances in genetics, proteomics, imaging, and artificial intelligence, which offer opportunities for the early detection of curable pancreatic neoplasms.

EXPERT OPINION

From exosomes, to circulating tumor DNA, to subtle changes on imaging, we know much more now about the biology and clinical manifestations of early pancreatic neoplasia than we did just five years ago. The overriding challenge, however, remains the development of a practical approach to screen for a relatively rare, but deadly, disease that is often treated with complex surgery. It is our hope that future advances will bring us closer to an effective and financially sound approach for the early detection of pancreatic cancer and its precursors.

Blood-based protein biomarkers and red blood cell aggregation in pancreatic cancer

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is highly malignant with a low 5-year survival rate. Blood biomarkers may be of value for the noninvasive diagnosis of pancreatic cancer.

OBJECTIVE

This study assessed blood-based biomarkers and disturbances in red blood cell aggregation associated with pancreatic cancer.

METHODS

We studied 61 patients who underwent pancreatic resection. Of these 61 patients, 46 patients had PDAC, and 15 patients had inflammatory tumours. Serum VEGF, hypoxia-inducible factor (HIF-1α), elastin-derived peptides (EDPs), total sialic acid (TSA) and resistin levels were measured. Red blood cell aggregation was assessed by a laser-assisted optical rotational cell analyser.

RESULTS

VEGF (p < 0.000001), HIF-1α (p = 0.000002), resistin (p = 0.000349), EDP (p = 0.000089) and TSA (p = 0.000013) levels were significantly higher in the PDAC group than in the inflammatory tumour group. The aggregation index (AI), syllectogram amplitude (AMP) and threshold shear rate (γthr) were significantly higher in the PDAC group, whereas the aggregation half-time (t1/2) was lower than in the inflammatory tumour group. Multivariate analyses revealed that VEGF, TSA and EDP levels were variables that predicted PDAC. VEGF levels were the most powerful predictor of PDAC independent of CA 19-9 levels. The cut-off points for VEGF, TSA and EDP levels were 134.56 pg/ml, 109.11 mg/dl and 36.4 ng/ml, respectively, with sensitivities of 97.8%, 87% and 69.6%, respectively, and specificities of 86.7%, 86.7% and 93.3%, respectively.

CONCLUSION

This study indicated that there are significant differences in blood-based biomarkers for differentiating between PDAC and inflammatory tumours of the pancreas. We also confirmed that PDAC is associated with the excessive aggregation of RBCs.

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.