scholarly journals Soluble AXL is a novel blood marker for early detection of pancreatic ductal adenocarcinoma and differential diagnosis from chronic pancreatitis

EBioMedicine ◽  
2022 ◽  
Vol 75 ◽  
pp. 103797
Author(s):  
Neus Martínez-Bosch ◽  
Helena Cristóbal ◽  
Mar Iglesias ◽  
Meritxell Gironella ◽  
Luis Barranco ◽  
...  
2014 ◽  
Vol 2 (Suppl 1) ◽  
pp. P60 ◽  
Author(s):  
Julia Mayerle ◽  
Holger Kalthoff ◽  
Regina C Reszka ◽  
Beate Kamlage ◽  
Erik Peter ◽  
...  

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037267
Author(s):  
Dóra Illés ◽  
Emese Ivány ◽  
Gábor Holzinger ◽  
Klára Kosár ◽  
M Gordian Adam ◽  
...  

IntroductionPancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis with an overall 5-year survival of approximately 8%. The success in reducing the mortality rate of PDAC is related to the discovery of new therapeutic agents, and to a significant extent to the development of early detection and prevention programmes. Patients with new-onset diabetes mellitus (DM) represent a high-risk group for PDAC as they have an eightfold higher risk of PDAC than the general population. The proposed screening programme may allow the detection of PDAC in the early, operable stage. Diagnosing more patients in the curable stage might decrease the morbidity and mortality rates of PDAC and additionally reduce the burden of the healthcare.Methods and analysisThis is a prospective, multicentre observational cohort study. Patients ≥60 years old diagnosed with new-onset (≤6 months) diabetes will be included. Exclusion criteria are (1) Continuous alcohol abuse; (2) Chronic pancreatitis; (3) Previous pancreas operation/pancreatectomy; (4) Pregnancy; (5) Present malignant disease and (6) Type 1 DM. Follow-up visits are scheduled every 6 months for up to 36 months. Data collection is based on questionnaires. Clinical symptoms, body weight and fasting blood will be collected at each, carbohydrate antigen 19–9 and blood to biobank at every second visit. The blood samples will be processed to plasma and analysed with mass spectrometry (MS)-based metabolomics. The metabolomic data will be used for biomarker validation for early detection of PDAC in the high-risk group patients with new-onset diabetes. Patients with worrisome features will undergo MRI or endoscopic ultrasound investigation, and surgical referral depending on the radiological findings. One of the secondary end points is the incidence of PDAC in patients with newly diagnosed DM.Ethics and disseminationThe study has been approved by the Scientific and Research Ethics Committee of the Hungarian Medical Research Council (41085-6/2019). We plan to disseminate the results to several members of the healthcare system includining medical doctors, dietitians, nurses, patients and so on. We plan to publish the results in a peer-reviewed high-quality journal for professionals. In addition, we also plan to publish it for lay readers in order to maximalise the dissemination and benefits of this trial.Trial registration numberClinicalTrials.gov NCT04164602


2019 ◽  
Vol 89 (4) ◽  
pp. 842-851.e1 ◽  
Author(s):  
Sushrut S. Thiruvengadam ◽  
Judith Chuang ◽  
Robert Huang ◽  
Mohit Girotra ◽  
Walter G. Park

2020 ◽  
Vol 25 (2) ◽  
pp. 65-71
Author(s):  
Jae Hyuck Chang

More than 80% of patients with pancreatic ductal adenocarcinoma (PDA) present with symptomatic, surgically unresectable disease. If a “stage shift” from the current 20% resectable proportion to greater by early detection can be achieved, it will unequivocally lead to improved survival in this otherwise dismal disease. Although the goal of early detection of PDA is laudable, the relatively low prevalence PDA renders general population screening infeasible. To avoid the perils of overdiagnosis and to focus early detection efforts on individuals deemed to be at higher-than-average risk, we need to define those subsets of individuals, such as familial kindred and patients with precursor cystic lesions, chronic pancreatitis, and new-onset diabetes. The next step is to determine when and how often to conduct surveillance in the atrisk individuals and the modalities (biomarkers and imaging) that will be used in the surveillance and diagnostic settings, respectively. Nonetheless, vast challenges still remain in terms of validated blood-based biomarkers, imaging modality, and when and how often the surveillance.


2020 ◽  
Vol 158 (6) ◽  
pp. S-857
Author(s):  
SOUVIK GHATAK ◽  
Satoshi Nishiwada ◽  
Eunsung Jun ◽  
Fuminori Sonohara ◽  
Yasuhiro Kodera ◽  
...  

2016 ◽  
Vol 150 (4) ◽  
pp. S221
Author(s):  
Julia Mayerle ◽  
Regina C. Reszka ◽  
Beate Kamlage ◽  
Erik Peter ◽  
Sandra González Maldonado ◽  
...  

2020 ◽  
Vol 10 ◽  
Author(s):  
Mohamed Zaid ◽  
Dalia Elganainy ◽  
Prashant Dogra ◽  
Annie Dai ◽  
Lauren Widmann ◽  
...  

BackgroundPreviously, we characterized subtypes of pancreatic ductal adenocarcinoma (PDAC) on computed-tomography (CT) scans, whereby conspicuous (high delta) PDAC tumors are more likely to have aggressive biology and poorer clinical outcomes compared to inconspicuous (low delta) tumors. Here, we hypothesized that these imaging-based subtypes would exhibit different growth-rates and distinctive metabolic effects in the period prior to PDAC diagnosis.Materials and methodsRetrospectively, we evaluated 55 patients who developed PDAC as a second primary cancer and underwent serial pre-diagnostic (T0) and diagnostic (T1) CT-scans. We scored the PDAC tumors into high and low delta on T1 and, serially, obtained the biaxial measurements of the pancreatic lesions (T0-T1). We used the Gompertz-function to model the growth-kinetics and estimate the tumor growth-rate constant (α) which was used for tumor binary classification, followed by cross-validation of the classifier accuracy. We used maximum-likelihood estimation to estimate initiation-time from a single cell (10-6 mm3) to a 10 mm3 tumor mass. Finally, we serially quantified the subcutaneous-abdominal-fat (SAF), visceral-abdominal-fat (VAF), and muscles volumes (cm3) on CT-scans, and recorded the change in blood glucose (BG) levels. T-test, likelihood-ratio, Cox proportional-hazards, and Kaplan-Meier were used for statistical analysis and p-value <0.05 was considered significant.ResultsCompared to high delta tumors, low delta tumors had significantly slower average growth-rate constants (0.024 month−1 vs. 0.088 month−1, p<0.0001) and longer average initiation-times (14 years vs. 5 years, p<0.0001). α demonstrated high accuracy (area under the curve (AUC)=0.85) in classifying the tumors into high and low delta, with an optimal cut-off of 0.034 month−1. Leave-one-out-cross-validation showed 80% accuracy in predicting the delta-class (AUC=0.84). High delta tumors exhibited accelerated SAF, VAF, and muscle wasting (p <0.001), and BG disturbance (p<0.01) compared to low delta tumors. Patients with low delta tumors had better PDAC-specific progression-free survival (log-rank, p<0.0001), earlier stage tumors (p=0.005), and higher likelihood to receive resection after PDAC diagnosis (p=0.008), compared to those with high delta tumors.ConclusionImaging-based subtypes of PDAC exhibit distinct growth, metabolic, and clinical profiles during the pre-diagnostic period. Our results suggest that heterogeneous disease biology may be an important consideration in early detection strategies for PDAC.


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