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, BRCA...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Neoplasia: An International Journal for Oncology Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1476558625000089 |
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| author | Di Jin Najeeb Ullah Khan Wei Gu Huijun Lei Ajay Goel Tianhui Chen |
| author_facet | Di Jin Najeeb Ullah Khan Wei Gu Huijun Lei Ajay Goel Tianhui Chen |
| author_sort | Di Jin |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-3427c7a41e7a4dff89bc4b6973659739 |
| institution | Kabale University |
| issn | 1476-5586 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neoplasia: An International Journal for Oncology Research |
| spelling | doaj-art-3427c7a41e7a4dff89bc4b69736597392025-02-03T04:16:37ZengElsevierNeoplasia: An International Journal for Oncology Research1476-55862025-02-0160101129Informatics strategies for early detection and risk mitigation in pancreatic cancer patientsDi Jin0Najeeb Ullah Khan1Wei Gu2Huijun Lei3Ajay Goel4Tianhui Chen5Department 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, ChinaInstitute of Biotechnology & Genetic Engineering (Health Division), The University of Agriculture Peshawar, Peshawar, PO Box 25130, PakistanDepartment of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou 310022, China; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, China; Wenzhou Medical University, Wenzhou, 325000, ChinaDepartment of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou 310022, China; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, ChinaDepartment of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Biomedical Research Center, Monrovia, California, USA; City of Hope Comprehensive Cancer Center, Duarte, CA, USA; Corresponding author at: Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Biomedical Research Center, Monrovia, California, USA, City of Hope Comprehensive Cancer Center, Duarte, CA, USA.Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou 310022, China; Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, China; Corresponding author at: Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou 310022, China, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310018, China.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.http://www.sciencedirect.com/science/article/pii/S1476558625000089Pancreatic cancerBiomarkersLiquid biopsyMolecular diagnosticsPersonalized medicine |
| spellingShingle | Di Jin Najeeb Ullah Khan Wei Gu Huijun Lei Ajay Goel Tianhui Chen Informatics strategies for early detection and risk mitigation in pancreatic cancer patients Neoplasia: An International Journal for Oncology Research Pancreatic cancer Biomarkers Liquid biopsy Molecular diagnostics Personalized medicine |
| title | Informatics strategies for early detection and risk mitigation in pancreatic cancer patients |
| title_full | Informatics strategies for early detection and risk mitigation in pancreatic cancer patients |
| title_fullStr | Informatics strategies for early detection and risk mitigation in pancreatic cancer patients |
| title_full_unstemmed | Informatics strategies for early detection and risk mitigation in pancreatic cancer patients |
| title_short | Informatics strategies for early detection and risk mitigation in pancreatic cancer patients |
| title_sort | informatics strategies for early detection and risk mitigation in pancreatic cancer patients |
| topic | Pancreatic cancer Biomarkers Liquid biopsy Molecular diagnostics Personalized medicine |
| url | http://www.sciencedirect.com/science/article/pii/S1476558625000089 |
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