Cystic Fluid Total Proteins, Low-Density Lipoprotein Cholesterol, Lipid Metabolites, and Lymphocytes: Worrisome...

Objectives: Pancreatic cystic neoplasms (PCNs), particularly intraductal papillary mucinous neoplasms (IPMNs), present a challenge for their potential malignancy. Despite promising biomarkers like CEA, amylase, and glucose, our study investigates whether metabolic indices in blood and cystic fluids (CFs), in addition to lymphocyte subsets and hematopoietic stem/progenitor cells (HSPCs), can effectively differentiate between high- and low-risk PCNs. Materials and Methods: A total of 26 patients (11 males, mean age 69.5 ± 9 years) undergoing Endoscopic Ultrasound-guided Fine Needle Aspiration were consecutively enrolled. Analyses included blood, serum, and CF, assessing glucose, CEA, cholesterol (total, HDL, and LDL), and total proteins. Flow cytometry examined immunophenotyping in peripheral blood and cystic fluids. Mass spectrometry was used for the metabolomic analysis of CF. Sensitivity, specificity, and ROC analyses evaluated discriminatory power. Results: A total of 25 out of 26 patients had IPMN. Patients were categorized as low or high risk based on multidisciplinary evaluation of clinical, radiological, and endoscopic data. High-risk patients showed lower CF total proteins and LDL cholesterol (p = 0.005 and p = 0.031), with a marked reduction in CF lymphocytes (p = 0.005). HSCPs were absent in CF. In blood, high-risk patients showed increased non-MHC-restricted cytotoxic T cells (p = 0.019). The metabolomic analysis revealed significantly reduced middle and long-chain acyl carnitines (AcCa) and tryptophan metabolites in high-risk patients. ROC curves indicated comparable discriminant abilities for CF lymphocytes (AUC 0.868), CF total proteins (AUC 0.859), and CF LDL cholesterol (AUC 0.795). The highest performance was achieved by the AcCa 14:2 and 16:0 (AUC: 0.9221 and 0.8857, respectively). Conclusions: CF levels of glucose, CEA, LDL cholesterol, and total proteins together with lymphocyte counts are easy translational biomarkers that may support risk stratification of PCNs in IPMN patients and might be endorsed by metabolomic analysis. Further studies are required for potential clinical integration.