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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. What's new? Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, mainly due to lack of symptoms and late diagnosis. Currently, only a single, unsatisfactory biomarker (CA19‐9), is approved for earlier diagnosis. Thus there is an urgent need for more practical, cost‐effective tests. In this study, the authors used proximity extension assay (PEA) to develop a panel of eight plasma‐protein biomarkers that can distinguish early PDAC from healthy controls. Although further validation studies are needed, these results support the potential of targeted proteomics for early detection of PDAC. [ABSTRACT FROM AUTHOR]

Purpose: Only 3% to 28% of patients referred to the urology clinic for hematuria are diagnosed with bladder cancer. Cystoscopy leads to high diagnostic costs and a high patient burden. Therefore, to improve the selection of patients for cystoscopy and reduce costs and over testing we aimed to validate a recently developed diagnostic urine assay., Materials and Methods: Included in study were 200 patients from a total of 3 European countries who underwent cystoscopy for hematuria, including 97 with bladder cancer and 103 with nonmalignant findings. Voided urine samples were collected prior to cystoscopy. DNA was extracted and analyzed for mutations in FGFR3, TERT and HRAS, and methylation of OTX1, ONECUT2 and TWIST1. Logistic regression was used to analyze the association between predictor variables and bladder cancer., Results: Combining the methylation and mutation markers with age led to an AUC of 0.96 (95% CI 0.92-0.99) with 93% sensitivity and 86% specificity, and an optimism corrected AUC of 0.95. The AUC was higher for T1 or greater tumors compared to Ta tumors (0.99 vs 0.93). The AUC was also higher for high grade tumors compared to low grade tumors (1.00 vs 0.93). Overall negative predictive value was 99% based on the 5% to 10% prevalence of bladder cancer in patients with hematuria. This would lead to a 77% reduction in diagnostic cystoscopy., Conclusions: Analyzing hematuria patients for the risk of bladder cancer using novel molecular markers may lead to a reduction in diagnostic cystoscopy. Combining methylation analysis (OTX1, ONECUT2 and TWIST1) with mutation analysis (FGFR3, TERT and HRAS) and patient age resulted in a validated accurate prediction model., (Copyright © 2017 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.)