Exocrine pancreatic insufficiency (EPI), an important cause of maldigestion and malnutrition, results from primary pancreatic disease or is secondary to impaired exocrine pancreatic function. Although chronic pancreatitis is the most common cause of EPI, several additional causes exist. These include pancreatic tumors, pancreatic resection procedures, and cystic fibrosis. Other diseases and conditions, such as diabetes mellitus, celiac disease, inflammatory bowel disease, and advanced patient age, have also been shown to be associated with EPI, but the exact etiology of EPI has not been clearly elucidated in these cases. The causes of EPI can be divided into loss of pancreatic parenchyma, inhibition or inactivation of pancreatic secretion, and postcibal pancreatic asynchrony. Pancreatic enzyme replacement therapy (PERT) is indicated for the conditions described above presenting with clinically clear steatorrhea, weight loss, or symptoms related to maldigestion and malabsorption. This review summarizes the current literature concerning those etiologies of EPI less common than chronic pancreatitis, the pathophysiology of the mechanisms of EPI associated with each diagnosis, and treatment recommendations.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal and aggressive cancers with a less than 6% five-year survival rate. Circulating microRNAs (miRNAs) are emerging as a useful tool for non-invasive diagnosis and prognosis estimation in the various cancer types, including PDAC. Our study aimed to evaluate whether miRNAs in the pre-operative blood plasma specimen have the potential to predict the prognosis of PDAC patients. In total, 112 PDAC patients planned for surgical resection were enrolled in our prospective study. To identify prognostic miRNAs, we used small RNA sequencing in 24 plasma samples of PDAC patients with poor prognosis (overall survival (OS) < 16 months) and 24 plasma samples of PDAC patients with a good prognosis (OS > 20 months). qPCR validation of selected miRNA candidates was performed in the independent cohort of PDAC patients (n = 64). In the discovery phase of the study, we identified 44 miRNAs with significantly different levels in the plasma samples of the group of good and poor prognosis patients. Among these miRNAs, 23 showed lower levels, and 21 showed higher levels in plasma specimens from PDAC patients with poor prognosis. Eleven miRNAs were selected for the validation, but only miR-99a-5p and miR-365a-3p were confirmed to have significantly lower levels and miR-200c-3p higher levels in plasma samples of poor prognosis cases. Using the combination of these 3-miRNA levels, we were able to identify the patients with poor prognosis with sensitivity 85% and specificity 80% (Area Under the Curve = 0.890). Overall, 3-miRNA prognostic score associated with OS was identified in the pre-operative blood plasma samples of PDAC patients undergoing surgical resection. Following further independent validations, the detection of these miRNA may enable identification of PDAC patients who have no survival benefit from the surgical treatment, which is associated with the high morbidity rates.

Pancreas is a vital gland of gastrointestinal system with exocrine and endocrine secretory functions, interweaved into essential metabolic circuitries of the human body. Pancreatic ductal adenocarcinoma (PDAC) represents one of the most lethal malignancies, with a 5-year survival rate of 11%. This poor prognosis is primarily attributed to the absence of early symptoms, rapid metastatic dissemination, and the limited efficacy of current therapeutic interventions. Despite recent advancements in understanding the etiopathogenesis and treatment of PDAC, there remains a pressing need for improved individualized models, identification of novel molecular targets, and development of unbiased predictors of disease progression. Here we aim to explore the concept of precision medicine utilizing 3-dimensional, patient-specific cellular models of pancreatic tumors and discuss their potential applications in uncovering novel druggable molecular targets and predicting clinical parameters for individual patients.