Advances in AI-driven applications of metal-organic frameworks for the diagnosis and treatment of pancreatic cancer

IF 4.2 3区工程技术 Q2 CHEMISTRY, APPLIED

Dyes and Pigments Pub Date : 2025-06-11 DOI:10.1016/j.dyepig.2025.112957

Chunyue Shi , Geqi Chen , Min Ye , Ziqi Xia , Yanna Ye , Aparna Kushwaha , Jun Wang , Abhinav Kumar , Ying Pan

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Abstract

Pancreatic cancer is known as the “king of cancers” due to pose early diagnostic challenges, high aggressiveness, and drug-resistance. Hence, with its rising incidence, innovative approaches are desirable for its diagnosis and treatment. Metal-organic frameworks (MOFs), characterized by their high specific surface area, tunable pore structure, biocompatibility, and multifunctional modification potential, are not only widely applied across various fields but have also demonstrated unique advantages in the diagnosis and treatment of pancreatic cancer in recent years. This review provides an overview of recent progress in the use of MOFs for the diagnosis and treatment of pancreatic cancer, as well as advancements in developing increasingly precise diagnostic and therapeutic strategies with the aid of artificial intelligence (AI). In diagnostics, the review discusses the isolation and detection of pancreatic cancer markers, followed by a focus on MOF-based methods such as MRI, biochemical sensors, and beyond. In terms of therapy, MOF-based treatments for pancreatic cancer are categorized into monotherapies (including acoustic kinetic therapy, photothermal therapy, and chemodynamic therapy), combination therapies, immunotherapies, and other approaches (such as iron-induced apoptosis and drug-delivery systems), highlighting the advancements enabled by MOFs in various treatment modalities. Finally, the integration of AI with MOFs introduces a new paradigm in the diagnosis and treatment of pancreatic cancer. In summary, metal-organic frameworks hold great promise for improving the accuracy and effectiveness of pancreatic cancer diagnosis and treatment, especially when combined with AI technologies.

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人工智能驱动的金属有机框架在胰腺癌诊断和治疗中的应用进展

胰腺癌因其早期诊断困难、高侵袭性和耐药性而被称为“癌症之王”。因此，随着其发病率的上升，需要创新的诊断和治疗方法。金属有机骨架（Metal-organic frameworks, mof）具有高比表面积、可调节的孔隙结构、生物相容性和多功能修饰潜力等特点，近年来不仅在各个领域得到广泛应用，而且在胰腺癌的诊断和治疗中也显示出独特的优势。本文综述了mof用于胰腺癌诊断和治疗的最新进展，以及在人工智能（AI）的帮助下开发越来越精确的诊断和治疗策略的进展。在诊断方面，本文讨论了胰腺癌标志物的分离和检测，然后重点介绍了基于mof的方法，如MRI、生化传感器等。在治疗方面，基于mof的胰腺癌治疗分为单一疗法（包括声动力学疗法、光热疗法和化学动力学疗法）、联合疗法、免疫疗法和其他方法（如铁诱导细胞凋亡和药物传递系统），突出了mof在各种治疗方式中所取得的进展。最后，人工智能与mof的结合为胰腺癌的诊断和治疗引入了一种新的范式。综上所述，金属有机框架在提高胰腺癌诊断和治疗的准确性和有效性方面具有很大的前景，特别是与人工智能技术相结合时。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Dyes and Pigments 工程技术-材料科学：纺织

CiteScore

8.20

自引率

13.30%

发文量

933

审稿时长

33 days

期刊介绍： Dyes and Pigments covers the scientific and technical aspects of the chemistry and physics of dyes, pigments and their intermediates. Emphasis is placed on the properties of the colouring matters themselves rather than on their applications or the system in which they may be applied. Thus the journal accepts research and review papers on the synthesis of dyes, pigments and intermediates, their physical or chemical properties, e.g. spectroscopic, surface, solution or solid state characteristics, the physical aspects of their preparation, e.g. precipitation, nucleation and growth, crystal formation, liquid crystalline characteristics, their photochemical, ecological or biological properties and the relationship between colour and chemical constitution. However, papers are considered which deal with the more fundamental aspects of colourant application and of the interactions of colourants with substrates or media. The journal will interest a wide variety of workers in a range of disciplines whose work involves dyes, pigments and their intermediates, and provides a platform for investigators with common interests but diverse fields of activity such as cosmetics, reprographics, dye and pigment synthesis, medical research, polymers, etc.