A novel early cancer detection approach for pancreatic cancer.

Abstract

613 Background: Pancreatic adenocarcinoma (PDAC) is commonly diagnosed at advanced stages, leading to high mortality rates. Earlier detection of PDAC is associated with improved long-term survival, but effective population-level screening is not available. There is therefore an urgent need to improve early detection of PDAC. Wholomics has developed a PDAC-specific proprietary early detection test, using cancer-specific molecular signatures in peripheral blood. Methods: We conducted a retrospective analysis of serum samples from the Amsterdam UMC Liquid Biopsy Center. Three cohorts were included in this study: 1) A cohort of healthy control subjects, 2) patients with a histopathologically confirmed diagnosis of PDAC spanning stages I through IV, and 3) patients with a confirmed diagnosis of chronic pancreatitis. Peripheral blood samples of cancer patients were taken before treatment or surgery. Wholomics used its proprietary technology to quantitatively analyse all serum specimens. Disease-specific molecular signatures were identified and used to develop computational biomarkers specific to both pancreatic pathologies (chronic pancreatitis and pancreatic cancer) and to pancreatic cancer individually. A comparative analysis was conducted employing multiple machine learning algorithms, which were subjected to a 10-fold cross-validation procedure. The accuracy, specificity and sensitivity of the best-performing algorithm is reported. Results: This retrospective study included 50 healthy controls, 12 patients with chronic pancreatitis, and 42 patients with pancreatic cancer (12 stage I, 15 stage II, 9 stage III, 6 stage IV). Applying Wholomics´ technology, an accuracy of 99.1% in differentiating the chronic pancreatitis and pancreatic cancer patients from the healthy controls was achieved. A specificity of 98.0% and a sensitivity of 100.0% were reached. Furthermore, pancreatic cancer patients and chronic pancreatitis patients were differentiated with 95.2% accuracy. Wholomics was also capable of differentiating between early stage (stages I and II) and late-stage (stages III and IV) pancreatic cancer with an accuracy of 100%. Conclusions: Taken together, this study demonstrates that disease-specific molecular signatures in peripheral blood can distinguish patients with PDAC from healthy individuals and patients with pancreatitis with very high accuracy. If validated in additional cohorts, this method could be evaluated as a screening test for PDAC to allow for early detection and improve patient outcomes.