Jin Di, Khan Najeeb Ullah, Gu Wei, Lei Huijun, Goel Ajay, Chen Tianhui
Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou 310022, China; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, China; Zhejiang Chinese Medical University, Hangzhou 310053, China.
Institute of Biotechnology & Genetic Engineering (Health Division), The University of Agriculture Peshawar, Peshawar, PO Box 25130, Pakistan.
Neoplasia. 2025 Feb;60:101129. doi: 10.1016/j.neo.2025.101129. Epub 2025 Jan 21.
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.
本综述全面概述了胰腺癌（PC）筛查、诊断和早期检测的当前状况。这强调了对高危人群进行靶向筛查的必要性，特别是那些具有家族易感性和基因突变的人群，如BRCA1、BRCA2和PALB2。本综述强调了大多数PC病例的散发性本质以及重要的风险因素，包括吸烟、饮酒、肥胖和糖尿病。已经讨论了先进的成像技术，如内镜超声（EUS）和对比增强谐波成像（CEH-EUS）在早期检测中的卓越敏感性。本综述还探讨了新型生物标志物的潜力，包括在体液（如血清、血浆、尿液和胆汁）中发现的生物标志物，以及液体活检技术在分析循环肿瘤DNA（ctDNA）、循环肿瘤细胞（CTC）和外泌体方面的新兴作用。以人工智能驱动的方法，如费利克斯项目和癌症SEEK中采用的方法，因其通过深度学习和生物标志物发现增强早期检测的潜力而受到关注。本综述强调了普遍基因检测以及将人工智能与传统诊断方法相结合以改善高危个体预后的重要性。此外，本综述指出了PC诊断的未来方向，包括下一代成像、分子生物标志物和个性化医学，旨在克服当前的诊断挑战并提高生存率。最终，该综述提倡采用信息学和人工智能驱动的策略来加强早期检测、降低发病率并在抗击胰腺癌中挽救生命。
