Intraductal papillary mucinous neoplasm to pancreas ductal adenocarcinoma sequence and pancreas cancer screening

Droplet digital polymerase chain reaction detection of KRAS mutations in pancreatic FNA samples: Technical and practical aspects for routine clinical implementation

BACKGROUND

Pancreatic adenocarcinoma (PDAC) is associated with a 5-year survival rate of less than 6%, and current treatments have limited efficacy. The diagnosis of PDAC is mainly based on a cytologic analysis of endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) samples. However, the collected specimens may prove noncontributory in a significant number of cases, delaying patient management and treatment. The combination of EUS-FNA sample examination and KRAS mutation detection can improve the sensitivity for diagnosis. In this context, the material used for molecular analysis may condition performance.

METHODS

The authors prospectively compared the performance of cytologic analysis combined with a KRAS droplet digital polymerase chain reaction (ddPCR) assay for PDAC diagnosis using either conventional formalin-fixed, paraffin-embedded cytologic samples or needle-rinsing fluids.

RESULTS

Molecular testing of formalin-fixed, paraffin-embedded cytologic samples was easier to set up, but the authors observed that the treatment of preanalytic samples, in particular the fixation process, drastically reduced ddPCR sensitivity, increasing the risk of false-negative results. Conversely, the analysis of dedicated, fresh needle-rinsing fluid samples appeared to be ideal for ddPCR analysis; it had greater sensitivity and was easily to implement in clinical use. In particular, fluid collection by the endoscopist, transportation to the laboratory, and subsequent freezing did not affect DNA quantity or quality. Moreover, the addition of KRAS mutation detection to cytologic examination improved diagnosis performance, regardless of the source of the sample.

CONCLUSIONS

Considering all of these aspects, the authors propose the use of an integrated flowchart for the KRAS molecular testing of EUS-FNA samples in clinical routine.

A Rare Case of a Pancreatic Intraductal Oncocytic Papillary Neoplasm Associated With Invasive Adenocarcinoma Presenting as a Gastric Mass

The World Health Organization recently recognized intraductal oncocytic papillary neoplasms of the pancreas (IOPNs) as distinct, pre-malignant pancreatic neoplasms. Due to their unique macroscopic and microscopic features, IOPNs are typically easy to diagnose and yield an indolent prognostic outcome. The diagnosis may be more complicated, and the prognosis may differ if an associated invasive carcinoma is present. Owing to the rarity of this entity, the available data is severely limited. Herein, we report a diagnostically challenging case of an IOPN associated with invasive carcinoma, initially presenting as a gastric mass with distinctive radiological and histopathological features.

Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer

The multi-modal and unstructured nature of observational data in Electronic Health Records (EHR) is currently a significant obstacle for the application of machine learning towards risk stratification. In this study, we develop a deep learning framework for incorporating longitudinal clinical data from EHR to infer risk for pancreatic cancer (PC). This framework includes a novel training protocol, which enforces an emphasis on early detection by applying an independent Poisson-random mask on proximal-time measurements for each variable. Data fusion for irregular multivariate time-series features is enabled by a "grouped" neural network (GrpNN) architecture, which uses representation learning to generate a dimensionally reduced vector for each measurement set before making a final prediction. These models were evaluated using EHR data from Columbia University Irving Medical Center-New York Presbyterian Hospital. Our framework demonstrated better performance on early detection (AUROC 0.671, CI 95% 0.667 - 0.675, p < 0.001) at 12 months prior to diagnosis compared to a logistic regression, xgboost, and a feedforward neural network baseline. We demonstrate that our masking strategy results greater improvements at distal times prior to diagnosis, and that our GrpNN model improves generalizability by reducing overfitting relative to the feedforward baseline. The results were consistent across reported race. Our proposed algorithm is potentially generalizable to other diseases including but not limited to cancer where early detection can improve survival.

Inherited predisposition to pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer death in the US by 2030. There are multiple germline pathogenic variants and cancer syndromes associated with an increased risk of PDAC. Precision treatment, informed by germline genetic testing and molecular tumor analysis, can optimize therapeutic regimens and outcomes for those diagnosed with PDAC. As a result, the National Comprehensive Cancer Network currently recommends genetic testing for all newly diagnosed PDAC patients given the clinical implications for treatment but also for the identification of at-risk family members who can benefit from pancreatic cancer screening and other cancer prevention strategies. This article reviews inherited risk factors for the development of PDAC and current screening strategies for the early detection of PDAC in high-risk populations.

Intestinal phenotype is maintained by Atoh1 in the cancer region of intraductal papillary mucinous neoplasm

Intraductal papillary mucinous neoplasm (IPMN) is a precancerous lesion of pancreatic cancer. Although there are 4 types of IPMN, among which intestinal-type IPMN is likely to progress into invasive cancer known as colloid carcinoma, no information regarding the involvement of the intestinal phenotype in the carcinogenesis of IPMN exists. The present study was conducted to explore how the intestinal differentiation system is maintained during the tumor progression of intestinal-type IPMN using surgical resection specimens. Results showed that Atoh1, a critical transcriptional factor for intestinal differentiation toward the secretory lineages of intestinal epithelial cells, was expressed in an invasive-grade IPMN. To determine the function of Atoh1 in pancreatic cancer, we generated a pancreatic ductal adenocarcinoma (PDAC) cell line overexpressing Atoh1. In a xenograft model, we successfully induced an IPMN phenotype in PDAC cells via Atoh1 induction. Finally, for the first time, we discovered that GPA33 is expressed in intestinal-type IPMN, thereby suggesting a novel target for cancer therapy. In conclusion, the intestinal differentiation system might be maintained during tumor progression of intestinal-type IPMN. Further analysis of the function of Atoh1 in IPMN might be useful for understanding the molecular mechanism underlying the malignant potential during the tumor progression of IPMN.

Pancreatic Fat Infiltration Is Associated with a Higher Risk of Pancreatic Ductal Adenocarcinoma

Background

Pancreatic ductal adenocarcinoma (PDAC) has a poor survival rate, partly due to delayed diagnosis. Identifying high-risk individuals could lead to early detection and improve survival. A number of risk factors such as alcohol consumption and metabolic syndrome are associated with fatty infiltration of the pancreas. Experimental models show that a fatty pancreas promotes tissue inflammation and fibrosis, which could promote PDAC.

Methods

We conducted a case-control study in a single-university tertiary hospital. Sixty-eight PDAC cases with recent non-contrast computed tomography (CT) and 235 controls were studied. The controls had no history of malignancy and underwent CT colonography for cancer screening in the same period. Pancreatic fat was estimated by calculating pancreatic (P) attenuation, corrected to splenic (S) attenuation, measured in three 1.0-cm² regions of the pancreas. The P.S100 value calculated was used to estimate fatty infiltration of the pancreas (FIP), with a lower P.S100 representing a higher FIP.

Results

The PDAC patients had a lower BMI and a higher rate of type 2 diabetes mellitus. The P.S100 was lower in cases than in controls (86.452 vs. 92.414, p = 4.016e-06), suggesting that FIP is higher with PDAC. The risk of developing PDAC steadily increased significantly for the quartiles with a higher FIP compared to the low FIP quartile. No correlation between BMI and FIP (r = -0.1031179; 95% confidence interval [CI] -0.22267106 to 0.01949092) was found. Adjusting for confounders (age, sex, BMI, and DM), the risk of developing PDAC according to the FIP was estimated to be 3.75 (95% CI 1.9234408-7.993337; p = 0.000171). FIP was stable before and after the diagnosis of PDAC in 9 cases with prior CT scans when no pancreatic tumor was identifiable.

Conclusion

Fatty pancreas is associated with an increased risk of pancreatic cancer. Once confirmed in larger-scale studies, these findings could help to identify at-risk individuals, particularly in high-risk groups such as chronic alcohol consumers.