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ObjectiveDNA-based testing of pancreatic cyst fluid (PCF) is a useful adjunct to the evaluation of pancreatic cysts (PCs). Mutations in KRAS/GNAS are highly specific for intraductal papillary mucinous neoplasms (IPMNs) and mucinous cystic neoplasms (MCNs), while TP53/PIK3CA/PTEN alterations are associated with advanced neoplasia. A prospective study was performed to evaluate preoperative PCF DNA testing.DesignOver 43-months, 626 PCF specimens from 595 patients were obtained by endoscopic ultrasound (EUS)-fine needle aspiration and assessed by targeted next-generation sequencing (NGS). Molecular results were correlated with EUS findings, ancillary studies and follow-up. A separate cohort of 159 PCF specimens was also evaluated for KRAS/GNAS mutations by Sanger sequencing.Results KRAS/GNAS mutations were identified in 308 (49%) PCs, while alterations in TP53/PIK3CA/PTEN were present in 35 (6%) cases. Based on 102 (17%) patients with surgical follow-up, KRAS/GNAS mutations were detected in 56 (100%) IPMNs and 3 (30%) MCNs, and associated with 89% sensitivity and 100% specificity for a mucinous PC. In comparison, KRAS/GNAS mutations by Sanger sequencing had a 65% sensitivity and 100% specificity. By NGS, the combination of KRAS/GNAS mutations and alterations in TP53/PIK3CA/PTEN had an 89% sensitivity and 100% specificity for advanced neoplasia. Ductal dilatation, a mural nodule and malignant cytopathology had lower sensitivities (42%, 32% and 32%, respectively) and specificities (74%, 94% and 98%, respectively).ConclusionsIn contrast to Sanger sequencing, preoperative NGS of PCF for KRAS/GNAS mutations is highly sensitive for IPMNs and specific for mucinous PCs. In addition, the combination of TP53/PIK3CA/PTEN alterations is a useful preoperative marker for advanced neoplasia.

The earlier diagnosis of cancer is one of the keys to reducing cancer deaths in the future. Here we describe our efforts to develop a noninvasive blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinomas and 182 control patients without known cancer. KRAS mutations were detected in the plasma of 66 patients (30%), and every mutation found in the plasma was identical to that subsequently found in the patient’s primary tumor (100% concordance). The use of KRAS in conjunction with four thresholded protein biomarkers increased the sensitivity to 64%. Only one of the 182 plasma samples from the control cohort was positive for any of the DNA or protein biomarkers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

Chronic pancreatitis (CP) has a profound independent effect on quality of life (QOL). Our aim was to identify factors that impact the QOL in CP patients. We used data on 1,024 CP patients enrolled in the three NAPS2 studies. Information on demographics, risk factors, co-morbidities, disease phenotype, and treatments was obtained from responses to structured questionnaires. Physical and mental component summary (PCS and MCS, respectively) scores generated using responses to the Short Form-12 (SF-12) survey were used to assess QOL at enrollment. Multivariable linear regression models determined independent predictors of QOL. Mean PCS and MCS scores were 36.7±11.7 and 42.4±12.2, respectively. Significant (P<0.05) negative impact on PCS scores in multivariable analyses was noted owing to constant mild-moderate pain with episodes of severe pain or constant severe pain (10 points), constant mild-moderate pain (5.2), pain-related disability/unemployment (5.1), current smoking (2.9 points), and medical co-morbidities. Significant (P<0.05) negative impact on MCS scores was related to constant pain irrespective of severity (6.8-6.9 points), current smoking (3.9 points), and pain-related disability/unemployment (2.4 points). In women, disability/unemployment resulted in an additional 3.7 point reduction in MCS score. Final multivariable models explained 27% and 18% of the variance in PCS and MCS scores, respectively. Etiology, disease duration, pancreatic morphology, diabetes, exocrine insufficiency, and prior endotherapy/pancreatic surgery had no significant independent effect on QOL. Constant pain, pain-related disability/unemployment, current smoking, and concurrent co-morbidities significantly affect the QOL in CP. Further research is needed to identify factors impacting QOL not explained by our analyses.

Immunoassay based bioanalytical measurements are widely used in a variety of biomedical research and clinical settings. In these settings they are assumed to faithfully represent the experimental conditions being tested and the sample groups being compared. Although significant technical advances have been made in improving sensitivity and quality of the measurements, currently no metrics exist that objectively quantify the fidelity of the measured analytes with respect to noise associated with the specific assay. Here we introduce ratio of cross -coefficient-of-variation ( rx COV), a fidelity metric for objectively assessing immunoassay analyte measurement quality when comparing its differential expression between different sample groups or experimental conditions. We derive the metric from first principles and establish its feasibility and applicability using simulated and experimental data. We show that rx COV assesses fidelity independent of statistical significance, and importantly, identifies when latter is meaningful. We also discuss its importance in the context of averaging experimental replicates for increasing signal to noise ratio. Finally, we demonstrate its application in a Lynch Syndrome case study. We conclude by discussing its applicability to multiplexed immunoassays, other biosensing assays, and to paired and unpaired data. We anticipate rx COV to be adopted as a simple and easy-to-use fidelity metric for performing robust and reproducible biomedical research.

Genomic DNA is folded into a higher-order structure that regulates transcription and maintains genomic stability. Although progress has been made on understanding biochemical characteristics of epigenetic modifications in cancer, the in-situ higher-order folding of chromatin structure during malignant transformation remains largely unknown. Here, using optimized stochastic optical reconstruction microscopy (STORM) for pathological tissue (PathSTORM), we uncover a gradual decompaction and fragmentation of higher-order chromatin folding throughout all stages of carcinogenesis in multiple tumor types, and prior to tumor formation. Our integrated imaging, genomic, and transcriptomic analyses reveal functional consequences in enhanced transcription activities and impaired genomic stability. We also demonstrate the potential of imaging higher-order chromatin disruption to detect high-risk precursors that cannot be distinguished by conventional pathology. Taken together, our findings reveal gradual decompaction and fragmentation of higher-order chromatin structure as an enabling characteristic in early carcinogenesis to facilitate malignant transformation, which may improve cancer diagnosis, risk stratification, and prevention. Aberrant chromatin structure is often found in cancer. Here, the authors optimise super-resolution microscopy for pathological tissue and discovered a significant decompaction of chromatin folding in early carcinogenesis prior to tumour formation.

The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively associated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP) of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN) levels of 32.4% and 29.7% in samples collected <1 and >1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combinations offered advantage over CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis. However, the efficacy of biomarker-based tools remains limited at present. Several biomarkers demonstrated significant velocity related to time to diagnosis, an observation which may offer considerable potential for enhancements in early detection.

Pancreatic cancer (PC) is a lethal malignancy that lacks specific diagnostic markers. The present study explores the diagnostic potential of the most differentially overexpressed secretory mucin MUC5AC alone and in combination with CA19-9 using multi-center training and validation sets. The expression of MUC5AC in benign pancreatic pathologies, PC precursor lesions, primary PC tissues and metastatic lesions was evaluated by immunohistochemistry. Circulating MUC5AC levels were measured using sandwich ELISA assay developed in-house, and CA19-9 was measured using radioimmunoassay. A combined training set (n=346) was used to evaluate the diagnostic (n=241) and predictive (n=105, total samples 201 from pre- and post-surgical and chemotherapy set) significance of MUC5AC. Results were further validated with a pre-defined cut-off value using independent sets from the Mayo Clinic (n=94) and the University of Pittsburgh Medical Center (n=321). Tissue expression analyses indicated the de novo expression of MUC5AC in pancreatic intraepithelial precursor lesions 1A (PanIN1A); the expression was maintained through all stages of progression to invasive adenocarcinoma. The median circulating MUC5AC levels in patients with resectable early-stage PC (EPC) (stage 1/2; 67.2 ng/ml, IQR: 23.9-382.1) and unresectable late-stage PC (LPC) (stage 3/4; 389.7 ng/ml, IQR: 87.7-948.6) were significantly higher compared with (P-value ≤0.0001) benign controls (BC) (7.2 ng/ml, IQR: 0.4-26.5) and (P-value ≤0.0001) chronic pancreatitis (CP) controls (8.4 ng/ml, IQR: 1.5-19.2). In the diagnostic training set (n=241), MUC5AC efficiently differentiated EPC from healthy controls (HC) (83%/80% sensitive (SN)/specific (SP)), BC (67%/87% SN/SP), and CP (83%/77% SN/SP). Independent validation sets from the Mayo Clinic and UPMC confirmed the diagnostic potential of MUC5AC to differentiate EPC from BC (68%/73%; 65%/83%) and CP (68%/79%; 65%/72%). Furthermore, MUC5AC and CA19-9 combination significantly improved (p-value < 0.001) the diagnostic accuracy for differentiating resectable cases from controls. MUC5AC is a valuable diagnostic biomarker, either alone or in combination with CA19-9, to differentiate PC from CP and benign controls.

CFTR is a dynamically regulated anion channel. Intracellular WNK1-SPAK activation causes CFTR to change permeability and conductance characteristics from a chloride-preferring to bicarbonate-preferring channel through unknown mechanisms. Two severe CFTR mutations (CFTRsev) cause complete loss of CFTR function and result in cystic fibrosis (CF), a severe genetic disorder affecting sweat glands, nasal sinuses, lungs, pancreas, liver, intestines, and male reproductive system. We hypothesize that those CFTR mutations that disrupt the WNK1-SPAK activation mechanisms cause a selective, bicarbonate defect in channel function (CFTRBD) affecting organs that utilize CFTR for bicarbonate secretion (e.g. the pancreas, nasal sinus, vas deferens) but do not cause typical CF. To understand the structural and functional requirements of the CFTR bicarbonate-preferring channel, we (a) screened 984 well-phenotyped pancreatitis cases for candidate CFTRBD mutations from among 81 previously described CFTR variants; (b) conducted electrophysiology studies on clones of variants found in pancreatitis but not CF; (c) computationally constructed a new, complete structural model of CFTR for molecular dynamics simulation of wild-type and mutant variants; and (d) tested the newly defined CFTRBD variants for disease in non-pancreas organs utilizing CFTR for bicarbonate secretion. Nine variants (CFTR R74Q, R75Q, R117H, R170H, L967S, L997F, D1152H, S1235R, and D1270N) not associated with typical CF were associated with pancreatitis (OR 1.5, p = 0.002). Clones expressed in HEK 293T cells had normal chloride but not bicarbonate permeability and conductance with WNK1-SPAK activation. Molecular dynamics simulations suggest physical restriction of the CFTR channel and altered dynamic channel regulation. Comparing pancreatitis patients and controls, CFTRBD increased risk for rhinosinusitis (OR 2.3, p<0.005) and male infertility (OR 395, p<<0.0001). WNK1-SPAK pathway-activated increases in CFTR bicarbonate permeability are altered by CFTRBD variants through multiple mechanisms. CFTRBD variants are associated with clinically significant disorders of the pancreas, sinuses, and male reproductive system.

Tumor-derived extracellular vesicles (EVs) show great potential as biomarkers for several diseases, including pancreatic cancer, due to their roles in cancer development and progression. However, the challenge of utilizing EVs as biomarkers lies in their inherent heterogeneity in terms of size and concentration, making accurate quantification difficult, which is highly dependent on the isolation and quantification methods used. In our study, we compared three EV isolation techniques and two EV quantification methods. We observed variations in EV concentration, with approximately 1.5-fold differences depending on the quantification method used. Interestingly, all EV isolation techniques consistently yielded similar EV quantities, overall size distribution, and modal sizes. In contrast, we found a notable increase in total EV amounts in samples from pancreatic cancer cell lines, mouse models, and patient plasma, compared to non-cancerous conditions. Moreover, individual tumor-derived EVs exhibited at least a 3-fold increase in several EV biomarkers. Our data, obtained from EVs isolated using various techniques and quantified through different methods, as well as originating from various pancreatic cancer models, suggests that EV profiling holds promise for the identification of unique and cancer-specific biomarkers in pancreatic cancer.

While there has been some progress on discovering clinically validated biomarkers for early detection in pancreatic ductal adenocarcinoma (PDAC), several challenges remain. Most approaches rely on single-modality biomarkers with limited sensitivity and/or specificity. Using data from a multicenter study with an age-matched cohort (n = 203 with healthy controls n = 46, pancreatitis controls n = 36, and diagnosed cases n = 121), we developed a machine learning approach integrating 2,096 microRNAs, 125 metabolites, and CA19-9. Our method performs unsupervised selection of an optimal subset of biomarkers with maximal discriminatory power for diagnosis and early detection. In training data, the selected biomarker panel achieved area under the curve (AUC) and sensitivity when controlling specificity at . The classification results under the selected multimodal panel generalize well for validation samples. The panel outperforms recently proposed microRNA-based approaches and identifies key biomarkers (such as aminobutyric acid and homovanillic acid) with high classification importance. Decision tree–based cut-offs are derived to enhance clinical interpretability, revealing the association between the low aminobutyric acid level and non-cancer status. These results highlight the superior discriminative ability and interpretability of the proposed multimodal biomarker panel, offering a promising tool for PDAC diagnosis and early detection.