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Clinica chimica acta; international journal of clinical chemistry · 2026

Emerging nanoparticle approaches for early detection and therapeutic targeting of pancreatic cancer.

СтатьяОбзорНазвание и аннотация: Перевод в очереди
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Abuhassan Qamar, Al-Ameer Hamzeh J, Younis Shahad Mohammed Dhiaa, Rizaev Jasur, Kibriyeva Makhfirat, Salih Rasim M, Jaber Mohamed Adil

Аннотация

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies and is characterized by a poor overall survival rate largely because of its aggressive nature and frequent late-stage diagnosis. More than 80% of patients are diagnosed with unresectable disease at the time of presentation, underscoring the critical need for more effective detection and monitoring strategies. Conventional diagnostic methods, including imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI), often lack the sensitivity to identify small, early-stage tumors within the pancreas. Furthermore, the most widely used serum biomarker, carbohydrate antigen 19-9 (CA19-9), suffers from suboptimal sensitivity and specificity, limiting its utility for early risk assessment and screening. Recent studies have indicated that CA19-9 has a sensitivity of only 53% or 68% when predicting clinical presentation 12 or 24 months in advance, respectively, while maintaining 95% specificity. This diagnostic challenge has spurred significant research into nanotechnology, which offers novel solutions by enabling the detection of minuscule cancerous lesions and biomarkers at the molecular level. NPs can be engineered to overcome biological barriers, accumulate selectively in tumor tissue, and deliver potent contrast agents or therapeutic payloads, thereby increasing diagnostic accuracy and facilitating personalized treatment approaches. This review provides a comprehensive analysis of emerging nanoparticle-based strategies for PDAC detection and monitoring, covering advancements in imaging, theranostics, and liquid biopsies and their translation from preclinical models to clinical practice.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты