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Translation of a Protease Turnover Assay for Clinical Discrimination of Mucinous Pancreatic Cysts

ABSTRACT: The classification of pancreatic cyst fluids can provide a basis for the early detection of pancreatic cancer while eliminating unnecessary procedures. A candidate biomarker, gastricsin (pepsin C), was found to be present in potentially malignant mucinous pancreatic cyst fluids. A gastricsin activity assay using a magnetic bead-based platform has been developed using immobilized peptide substrates selective for gastricsin bearing a dimeric rhodamine dye. The unique dye structure allows quantitation of enzyme-cleaved product by both fluorescence and surface enhanced Raman spectroscopy (SERS). The performance of this assay was compared with ELISA assays of pepsinogen C and the standard of care, carcinoembryonic antigen (CEA), in the same clinical sample cohort. A retrospective cohort of mucinous (n = 40) and non-mucinous (n = 29) classes of pancreatic cyst fluid samples were analyzed using the new protease activity assay. For both assay detection modes, successful differentiation of mucinous and non-mucinous cyst fluid was achieved using 1 µL clinical samples. The activity-based assays in combination with CEA exhibit optimal sensitivity and specificity of 87% and 93%, respectively. The use of this gastricsin activity assay requires a minimal volume of clinical specimen, offers a rapid assay time, and shows improvements in the differentiation of mucinous and non-mucinous cysts using an accurate standardized readout of product formation, all without interfering with the clinical standard of care.

SUBMITTER: Suresh V

PROVIDER: S-EPMC9222202 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Project description:BackgroundPancreatic cystic fluid (PCF) analysis is frequently used for cyst diagnosis with carcinoembryonic antigen (CEA) being the most accepted biomarker. Low glucose levels in PCF were previously suggested as a marker for mucinous cysts. A bed-side glucometer is a point-of care, immediate, simple, and cheap method which requires a small volume of PCF.ObjectivesThe aim of our study was to identify the optimal glucose cut-off level for identifying mucinous cysts, evaluate the diagnostic accuracy of glucose compared to CEA, and validate glucometry against reference laboratory biochemical analysis.DesignA single-center prospective cohort study.MethodsConsecutive patients aged 18 and older, who underwent pancreatic cyst evaluation, at the Tel Aviv Medical Center between 2016 and 2021 were analyzed. Cyst type was defined based on clinical, laboratory, and radiologic findings. Glucose was measured using laboratory biochemical analysis and two glucometers. Receiver operating characteristic analysis derived sensitivity, specificity, and accuracy were calculated and McNemar test was used to compare between methods.ResultsOne hundred and one PCF samples were evaluated. The areas under the receiver operating characteristics curve for identifying mucinous cysts using glucometer, glucose laboratory, and their combination were 0.88 (p < 0.001), 0.92 (p < 0.001), and 0.93 (p < 0.001), respectively. A glucose level of 87 mg/dL was identified as the optimal laboratory glucose threshold value to detect mucinous cyst with a sensitivity of 90.9%, specificity of 83.3%, and accuracy of 89.3, higher in comparison to cyst fluid CEA. Furthermore, PCF glucose levels had the strongest association with mucinous cysts.ConclusionOur findings suggest that PCF glucose level is more accurate than CEA for the diagnosis of mucinous cysts. Glucometry glucose level assessment demonstrated an excellent correlation with laboratory glucose measurements and may become a useful diagnostic test.

Project description:BackgroundMore accurate diagnosis of mucinous cysts will reduce the risk of unnecessary pancreatic surgery. Carcinoembryonic antigen (CEA) and glucose in pancreatic cyst fluid (PCF) can differentiate mucinous from non-mucinous pancreatic cystic neoplasms (PCN). The current study assessed the value of combined CEA and glucose testing in PCF.MethodsCross-sectional validation study including prospectively collected PCF from patients undergoing endoscopic ultrasonography-guided fine-needle aspiration (EUS-FNA) and pancreatic surgery. We performed laboratory measurements for CEA and glucose and measured glucose levels by a hand glucometer. Primary outcome was diagnostic accuracy evaluated by receiver operator curves (ROC), sensitivity, specificity, positive, and negative predictive value (PPV, NPV).ResultsOverall, PCF was collected from 63 patients, including 33 (52%) with mucinous and 30 (48%) with non-mucinous PCN. Histopathology (n = 36; 57%), cytopathology (n = 2; 3%), or clinical and/or radiological diagnosis (n = 25; 40%) was used as reference standard. Combined CEA (cut-off ≥ 192 ng/ml) and laboratory glucose testing (cut-off ≤ 50 mg/dL) reached 92% specificity and 48% sensitivity, whereas either positive CEA (cut-off ≥ 20 ng/ml) or glucose testing (cut-off ≤ 50 mg/dL) showed 97% sensitivity and 50% specificity. Sensitivity and specificity were 80% and 68% for CEA ≥ 20 ng/mL versus 50% and 93% for CEA ≥ 192 ng/mL (the conventional cut-off level). Laboratory and glucometer glucose both reached 100% sensitivity and 60% and 45% specificity, respectively. None of the biomarkers and cut-offs reached a PPV exceeding 90%, whereas both glucose measurements had a NPV of 100% (i.e., high glucose excludes a mucinous cyst).ConclusionCombined CEA and glucose testing in PCF reached high specificity and sensitivity for differentiating mucinous from non-mucinous PCN. Glucose testing, whether alone or combined with the new CEA cut-off (≥ 20 ng/mL), reached > 95% sensitivity for mucinous cysts, whereas only glucose reached a NPV > 95%.

Project description:PurposeThis study aimed to develop and verify a multi-phase (MP) computed tomography (CT)-based radiomics nomogram to differentiate pancreatic serous cystic neoplasms (SCNs) from mucinous cystic neoplasms (MCNs), and to compare the diagnostic efficacy of radiomics models for different phases of CT scans.Materials and methodsA total of 170 patients who underwent surgical resection between January 2011 and December 2018, with pathologically confirmed pancreatic cystic neoplasms (SCN=115, MCN=55) were included in this single-center retrospective study. Radiomics features were extracted from plain scan (PS), arterial phase (AP), and venous phase (VP) CT scans. Algorithms were performed to identify the optimal features to build a radiomics signature (Radscore) for each phase. All features from these three phases were analyzed to develop the MP-Radscore. A combined model comprised the MP-Radscore and imaging features from which a nomogram was developed. The accuracy of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration tests, and decision curve analysis.ResultsFor each scan phase, 1218 features were extracted, and the optimal ones were selected to construct the PS-Radscore (11 features), AP-Radscore (11 features), and VP-Radscore (12 features). The MP-Radscore (14 features) achieved better performance based on ROC curve analysis than any single phase did [area under the curve (AUC), training cohort: MP-Radscore 0.89, PS-Radscore 0.78, AP-Radscore 0.83, VP-Radscore 0.85; validation cohort: MP-Radscore 0.88, PS-Radscore 0.77, AP-Radscore 0.83, VP-Radscore 0.84]. The combination nomogram performance was excellent, surpassing those of all other nomograms in both the training cohort (AUC, 0.91) and validation cohort (AUC, 0.90). The nomogram also performed well in the calibration and decision curve analyses.ConclusionsRadiomics for arterial and venous single-phase models outperformed the plain scan model. The combination nomogram that incorporated the MP-Radscore, tumor location, and cystic number had the best discriminatory performance and showed excellent accuracy for differentiating SCN from MCN.

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Translation of a Protease Turnover Assay for Clinical Discrimination of Mucinous Pancreatic Cysts

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