Di Jin , Najeeb Ullah Khan , Wei Gu , Huijun Lei , Ajay Goel , Tianhui Chen
{"title":"Informatics strategies for early detection and risk mitigation in pancreatic cancer patients","authors":"Di Jin , Najeeb Ullah Khan , Wei Gu , Huijun Lei , Ajay Goel , Tianhui Chen","doi":"10.1016/j.neo.2025.101129","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":18917,"journal":{"name":"Neoplasia","volume":"60 ","pages":"Article 101129"},"PeriodicalIF":4.8000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11763847/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neoplasia","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476558625000089","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Neoplasia publishes the results of novel investigations in all areas of oncology research. The title Neoplasia was chosen to convey the journal’s breadth, which encompasses the traditional disciplines of cancer research as well as emerging fields and interdisciplinary investigations. Neoplasia is interested in studies describing new molecular and genetic findings relating to the neoplastic phenotype and in laboratory and clinical studies demonstrating creative applications of advances in the basic sciences to risk assessment, prognostic indications, detection, diagnosis, and treatment. In addition to regular Research Reports, Neoplasia also publishes Reviews and Meeting Reports. Neoplasia is committed to ensuring a thorough, fair, and rapid review and publication schedule to further its mission of serving both the scientific and clinical communities by disseminating important data and ideas in cancer research.