Serum biomarkers for the differentiation of autoimmune pancreatitis from pancreatic ductal adenocarcinoma

Informatics strategies for early detection and risk mitigation in pancreatic cancer patients

This review provides a comprehensive overview of the current landscape in pancreatic cancer (PC) screening, diagnosis, and early detection. This emphasizes the need for targeted screening in high-risk groups, particularly those with familial predispositions and genetic mutations, such as BRCA1, BRCA2, and PALB2. This review highlights the sporadic nature of most PC cases and significant risk factors, including smoking, alcohol consumption, obesity, and diabetes. Advanced imaging techniques, such as Endoscopic Ultrasound (EUS) and Contrast-Enhanced Harmonic Imaging (CEH-EUS), have been discussed for their superior sensitivity in early detection. This review also explores the potential of novel biomarkers, including those found in body fluids, such as serum, plasma, urine, and bile, as well as the emerging role of liquid biopsy technologies in analyzing circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes. AI-driven approaches, such as those employed in Project Felix and CancerSEEK, have been highlighted for their potential to enhance early detection through deep learning and biomarker discovery. This review underscores the importance of universal genetic testing and the integration of AI with traditional diagnostic methods to improve outcomes in high-risk individuals. Additionally, this review points to future directions in PC diagnostics, including next-generation imaging, molecular biomarkers, and personalized medicine, aiming to overcome current diagnostic challenges and improve survival rates. Ultimately, the review advocates the adoption of informatics and AI-driven strategies to enhance early detection, reduce morbidity, and save lives in the fight against pancreatic cancer.

Unmet needs in biomarkers for autoimmune pancreatitis diagnosis

Autoimmune pancreatitis (AIP) is a rare chronic autoimmune disorder. The diagnosis of AIP mainly depends on histopathology, imaging and response to treatment. Serum immunoglobulin 4 (IgG4) is used only as collateral evidence in diagnostic criteria for AIP because of its moderate sensitivity. Serum IgG4 levels are normal in 15%-37% of type 1 AIP and most of type 2 AIP patients. In these patients, the indeterminate imaging and histopathology may lead to the difficulty in definitive diagnosis of AIP. Therefore, discovery of new biomarkers is important for AIP diagnosis. Here, we provide some views on the progression and challenges in identifying novel serological biomarkers in AIP diagnosis.