Pancreatic cyst fluid glucose: a rapid on-site diagnostic test for mucinous cysts
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ABSTRACT: Background:
Pancreatic cystic fluid (PCF) analysis is frequently used for cyst diagnosis
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PROVIDER: S-EPMC9638530 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
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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%.
| S-EPMC10156886 | biostudies-literature
Project description:Widespread use of cross-sectional imaging and increasing age of the general population has increased the number of detected pancreatic cystic lesions. However, several pathological entities with a variety in malignant potential have to be discriminated to allow clinical decision making. Discrimination between mucinous pancreatic cystic neoplasms (PCNs) and nonmucinous pancreatic lesions is the primary step in the clinical work-up, as malignant transformation is mostly associated with mucinous PCN. We performed a retrospective analysis of all resected PCN in our tertiary center from 2000 to 2014, to evaluate preoperative diagnostic performance and the results of implementation of the consensus guidelines over time. This was followed by a prospective cohort study of patients with an undefined pancreatic cyst, where the added value of cytopathological mucin evaluation to carcinoembryonic antigen (CEA) in cyst fluid for the discrimination of mucinous PCN and nonmucinous cysts was investigated. Retrospective analysis showed 115 patients operated for a PCN, with a correct preoperative classification in 96.2% of the patients. High-grade dysplasia or invasive carcinoma was observed in only 32.3% of mucinous PCN. In our prospective cohort (n = 71), 57.7% of patients were classified as having a mucinous PCN. CEA ≥ 192 ng/mL had an accuracy of 63.4%, and cytopathological mucin evaluation an accuracy of 73.0%. Combining these 2 tests further improved diagnostic accuracy of a mucinous PCN to 76.8%. CEA level and mucin evaluation were not predictive of the degree of dysplasia. These findings show that adding cytopathology to cyst fluid biochemistry improves discrimination between mucinous PCN and nonmucinous cysts.
| S-EPMC4616542 | biostudies-other
Project description:ObjectivesCurrent standard of care imaging, cytology, or cystic fluid analysis cannot reliably differentiate malignant from benign pancreatic cystic neoplasms. This study sought to determine if the metabolic profile of cystic fluid could distinguish benign and malignant lesions, as well as mucinous and non-mucinous lesions.MethodsMetabolic profiling by untargeted mass spectrometry and quantitative nuclear magnetic resonance was performed in 24 pancreatic cyst fluid from surgically resected samples with pathological diagnoses and clinicopathological correlation.Results(Iso)-butyrylcarnitine distinguished malignant from benign pancreatic cysts, with a diagnostic accuracy of 89%. (Iso)-butyrylcarnitine was 28-fold more abundant in malignant cyst fluid compared with benign cyst fluid (P=.048). Furthermore, 5-oxoproline (P=.01) differentiated mucinous from non-mucinous cysts with a diagnostic accuracy of 90%, better than glucose (82% accuracy), a previously described metabolite that distinguishes mucinous from non-mucinous cysts. Combined analysis of glucose and 5-oxoproline did not improve the diagnostic accuracy. In comparison, standard of care cyst fluid carcinoembryonic antigen (CEA) and cytology had a diagnostic accuracy of 40% and 60% respectively for mucinous cysts. (Iso)-butyrylcarnitine and 5-oxoproline correlated with cyst fluid CEA levels (P<.0001 and P<.05 respectively). For diagnosing malignant pancreatic cysts, the diagnostic accuracies of cyst size > 3 cm, ≥ 1 high-risk features, cyst fluid CEA, and cytology are 38%, 75%, 80%, and 75%, respectively.Conclusions(Iso)-butyrylcarnitine has potential clinical application for accurately distinguishing malignant from benign pancreatic cysts, and 5-oxoproline for distinguishing mucinous from non-mucinous cysts.
| S-EPMC8479274 | biostudies-literature
Project description:The diagnosis of pancreatic cystic lesions has increased dramatically. Most are benign, whereas some, such as intraductal papillary mucinous neoplasms (IPMN), represent precursors of pancreatic adenocarcinoma. Therapeutic stratification of IPMNs is challenging without precise information on dysplasia grade and presence of invasion. We assessed the diagnostic benefit of using miRNAs as biomarkers in pancreatic cyst fluid, focusing on IPMNs because of their frequency and malignant potential.RNA was extracted from 55 microdissected formalin-fixed, paraffin-embedded (FFPE) IPMN specimens, and 65 cyst fluid specimens aspirated following surgical resection. Expression of 750 miRNAs was evaluated with TaqMan miRNA Arrays using 22 FFPE and 15 cyst fluid specimens. Differential expression of selected miRNA candidates was validated in 33 FFPE and 50 cyst fluid specimens using TaqMan miRNA Assays.We identified 26 and 37 candidate miRNAs that distinguish low-grade from high-grade IPMNs using FFPE and cyst fluid specimens, respectively. A subset of 18 miRNAs, selected from FFPE and cyst fluid data, separated high-grade IPMNs from low-grade IPMNs, serous cystadenomas (SCA) and uncommon cysts, such as solid pseudopapillary neoplasms (SPN) and cystic pancreatic neuroendocrine tumors (PanNET). A logistic regression model using nine miRNAs allowed prediction of cyst pathology implying resection (high-grade IPMNs, PanNETs, and SPNs) versus conservative management (low-grade IPMNs, SCAs), with a sensitivity of 89%, a specificity of 100%, and area under the curve of 1.We found candidate miRNAs that helped identify patients with high-grade IPMN and exclude nonmucinous cysts. These classifiers will require validation in a prospective setting to ultimately confirm their clinical usefulness.
| S-EPMC3547600 | biostudies-literature
Project description:Telomere end-to-end fusions are an important source of chromosomal instability that arise in cells with critically shortened telomeres. We developed a nested real-time quantitative PCR method for telomere fusion detection in pancreatic ductal adenocarcinomas, intraductal papillary mucinous neoplasms (IPMNs), and IPMN cyst fluids. Ninety-one pancreatic cancer cell lines and xenograft samples, 93 IPMNs, and 93 surgically aspirated IPMN cyst fluid samples were analyzed. The association between telomere shortening, telomerase activity, and telomere fusion detection was evaluated. Telomere fusions were detected in 56 of 91 pancreatic cancers (61.5%). Telomere fusion-positive cell lines had significantly shorter telomere lengths than fusion-negative lines (P = 0.003). Telomere fusions were undetectable in normal pancreas or IPMNs with low-grade dysplasia (0.0%) and were detected in IPMN with high-grade dysplasia (HGD; 48.0%) (P < 0.001). In IPMN cyst fluids, telomere fusions were more frequent in IPMNs with HGD (26.9%) or associated invasive cancer (42.9%) than IPMN with intermediate-grade dysplasia (15.4%) or low-grade dysplasia (0%) (P = 0.025). Telomerase activity levels were higher in cyst fluids with fusions than in those without (P = 0.0414). Cyst fluid telomere fusion status was an independent predictor of HGD/invasive cancer by multivariate analysis (odds ratio, 6.23; 95% CI, 1.61-28.0). Telomere fusions are detected in later stages of IPMN progression and can serve as a marker for predicting the presence of HGD and/or invasive cancer.
| S-EPMC5745545 | biostudies-literature
Project description:A subset of pancreatic cystic neoplasms are regarded as precursor lesions of pancreatic cancer, but only a minority of all pancreatic cystic neoplasms will undergo malignant transformation. MicroRNAs are increasingly recognized as molecular targets in carcinogenesis. Previously, a 9-microRNA (miR) signature was suggested to discriminate between high risk and low risk pancreatic cystic neoplasm. In this study, we aimed to validate this 9-miR panel in a prospective cohort. Total miR was isolated from pancreatic cyst fluid and expression of miR18a, miR24, miR30a-3p, miR92a, miR99b, miR106b, miR142-3p, miR342-3p, and miR532-3p was analyzed by singleplex Taqman MicroRNA Assay. A total of 62 patient samples were analyzed. During follow-up, 24 (38.7%) patients underwent resection, of which 6 (9.7%) patients showed at least high grade dysplasia. A logistic regression model presented a "predicted risk" score which significantly differed between low and high risk cysts, either including all patients or only those with histological confirmation of diagnosis. Using a set cut-off of 50%, the sensitivity of the model for the total cohort was 10.0%, specificity 100.0%, positive predicted value 100.0%, negative predicted value 85.2%, and diagnostic accuracy of 85.5%. Thus, while observing a significant difference between low and high risk cysts, clinical implementation of this biomarker panel is as yet unlikely to be beneficial in the management of pancreatic cysts.
| S-EPMC5023405 | biostudies-literature
Project description:Integration of multi-omic data for the purposes of biomarker discovery can provide novel and robust panels across multiple biological compartments. Appropriate analytical methods are key to ensuring accurate and meaningful outputs in the multi-omic setting. Here, we extensively profile the proteome and transcriptome of patient pancreatic cyst fluid (PCF) (n=32) and serum (n=68), before integrating matched omic and biofluid data, to identify biomarkers of pancreatic cancer risk. Differential expression analysis, feature reduction, multi-omic data integration, unsupervised hierarchical clustering, principal component analysis, spearman correlations and leave-one-out cross-validation were performed using RStudio and CombiROC software. An 11-feature multi-omic panel in PCF [PIGR, S100A8, REG1A, LGALS3, TCN1, LCN2, PRSS8, MUC6, SNORA66, miR-216a-5p, miR-216b-5p] generated an AUC=0.80. A 13-feature multi-omic panel in serum [SHROOM3, IGHV3-72, IGJ, IGHA1, PPBP, APOD, SFN, IGHG1, miR-197-5p, miR-6741-5p, miR-3180, miR-3180-3p, miR-6782-5p] produced an AUC=0.824. Integration of the strongest performing biomarkers generated a 10-feature cross-biofluid multi-omic panel [S100A8, LGALS3, SNORA66, miR-216b-5p, IGHV3-72, IGJ, IGHA1, PPBP, miR-3180, miR-3180-3p] with an AUC=0.970. Multi-omic profiling provides an abundance of potential biomarkers. Integration of data from different omic compartments, and across biofluids, produced a biomarker panel that performs with high accuracy, showing promise for the risk stratification of these patients.
2025-01-06 | GSE280772 | GEO
Project description:BackgroundThe application of advanced imaging technologies for identifying pancreatic cysts has become widespread. However, accurately differentiating between low-grade dysplasia (LGD), high-grade dysplasia (HGD), and invasive intraductal papillary mucinous neoplasms (IPMNs) remains a diagnostic challenge with current biomarkers, necessitating the development of novel biomarkers that can distinguish IPMN malignancy.MethodsCyst fluid samples were collected from nine IPMN patients (3 LGD, 3 HGD, and 3 invasive IPMN) during their pancreatectomies. An integrated proteomics approach that combines filter-aided sample preparation, stage tip-based high-pH fractionation, and high-resolution MS was applied to acquire in-depth proteomic data of pancreatic cyst fluid and discover marker candidates for IPMN malignancy. Biological processes of differentially expressed proteins that are related to pancreatic cysts and aggressive malignancy were analyzed using bioinformatics tools such as gene ontology analysis and Ingenuity pathway analysis. In order to confirm the validity of the marker candidates, 19 cyst fluid samples were analyzed by western blot.ResultsA dataset of 2992 proteins was constructed from pancreatic cyst fluid samples. A subsequent analysis found 2963 identified proteins in individual samples, 2837 of which were quantifiable. Differentially expressed proteins between histological grades of IPMN were associated with pancreatic diseases and malignancy according to ingenuity pathway analysis. Eighteen biomarker candidates that were differentially expressed across IPMN histological grades were discovered-7 DEPs that were upregulated and 11 that were downregulated in more malignant grades. HOOK1 and PTPN6 were validated by western blot in an independent cohort, the results of which were consistent with our proteomic data.ConclusionsThis study demonstrates that novel biomarker candidates for IPMN malignancy can be discovered through proteomic analysis of pancreatic cyst fluid.
| S-EPMC5907296 | biostudies-literature
Project description:ObjectivesPancreatic cystic lesions (PCLs) may be precancerous. Those likely to harbor high-grade dysplasia (HGD) or pancreatic cancer (PC) are targets for surgical resection. Current algorithms to predict advanced neoplasia (HGD/PC) in PCLs lack diagnostic accuracy. In pancreatic tissue and cyst fluid (CF) from PCLs, we sought to identify and validate novel methylated DNA markers (MDMs) that discriminate HGD/PC from low-grade dysplasia (LGD) or no dysplasia (ND).MethodsFrom an unbiased whole-methylome discovery approach using predefined selection criteria followed by multistep validation on case (HGD or PC) and control (ND or LGD) tissues, we identified discriminant MDMs. Top candidate MDMs were then assayed by quantitative methylation-specific polymerase chain reaction on archival CF from surgically resected PCLs.ResultsOf 25 discriminant MDMs identified in tissue, 13 were selected for validation in 134 CF samples (21 cases [8 HGD, 13 PC], 113 controls [45 ND, 68 LGD]). A tree-based algorithm using 2 CF-MDMs (TBX15, BMP3) achieved sensitivity and specificity above 90%. Discrimination was significantly better by this CF-MDM panel than by mutant KRAS or carcinoembryonic antigen, with areas under the receiver operating characteristic curve of 0.93 (95% confidence interval: 0.86-0.99), 0.71 (0.57-0.85), and 0.72 (0.60-0.84), respectively. Cutoffs for the MDM panel applied to an independent CF validation set (31 cases, 56 controls) yielded similarly high discrimination, areas under the receiver operating characteristic curve = 0.86 (95% confidence interval: 0.77-0.94, P = 0.2).DiscussionNovel MDMs discovered and validated in tissue accurately identify PCLs harboring HGD/PC. A panel of 2 MDMs assayed in CF yielded results with potential to enhance current risk prediction algorithms. Prospective studies are indicated to optimize and further evaluate CF-MDMs for clinical use.
| S-EPMC7294458 | biostudies-literature
Project description:Biomarkers for the diagnostic classification of pancreatic cysts are urgently needed. Deregulated microRNA (miRNAs) expression is widespread in pancreatic cancer. We assessed whether aberrant miRNAs in pancreatic cyst fluid could be used as potential biomarkers for cystic precursor lesions of pancreatic cancer.Cyst fluid specimens were prospectively collected from 40 surgically resected pancreatic cysts, and small RNAs were extracted. The 'mucinous' cohort included 14 intraductal papillary mucinous neoplasms (including 3 with an associated adenocarcinoma) and 10 mucinous cystic neoplasms; the 'nonmucinous' cohort included 11 serous cystadenomas and 5 other benign cysts. Quantitative reverse transcription PCR was performed for five miRNAs (miR-21, miR-155, miR-221, miR-17-3p, miR-191), which were previously reported as overexpressed in pancreatic adenocarcinomas.Significantly higher expression of miR-21, miR-221, and miR-17-3p was observed in the mucinous versus nonmucinous cysts (p < 0.01), with the mean relative fold differences being 7.0-, 7.9-, and 5.4-fold, respectively. Receiver operating characteristic curves demonstrated the highest median area under the curve for miR-21, with a median specificity of 76%, at a sensitivity of 80%.This pilot study demonstrates that profiling miRNAs in pancreatic cyst fluid samples is feasible and can yield potential biomarkers for the classification of cystic lesions of the pancreas. and IAP.
| S-EPMC3142103 | biostudies-literature