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缺陷型 Fe 金属有机框架增强代谢组学分析,实现人类癌症的高精度诊断。

Defective Fe Metal-Organic Frameworks Enhance Metabolic Profiling for High-Accuracy Diagnosis of Human Cancers.

机构信息

State Key Laboratory for Oncogenes and Related Genes, Shanghai Key Laboratory of Gynecologic Oncology, Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China.

School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.

出版信息

Adv Mater. 2022 Jul;34(26):e2201422. doi: 10.1002/adma.202201422. Epub 2022 May 23.

DOI:10.1002/adma.202201422
PMID:35429018
Abstract

Cancers heavily threaten human life; therefore, a high-accuracy diagnosis is vital to protect human beings from the suffering of cancers. While biopsies and imaging methods are widely used as current technologies for cancer diagnosis, a new detection platform by metabolic analysis is expected due to the significant advantages of fast, simple, and cost-effectiveness with high body tolerance. However, the signal of molecule biomarkers is too weak to acquire high-accuracy diagnosis. Herein, precisely engineered metal-organic frameworks for laser desorption/ionization mass spectrometry, allowing favorable charge transfer within the molecule-substrate interface and mitigated thermal dissipation by adjusting the phonon scattering with metal nodes, are developed. Consequently, a surprising signal enhancement of ≈10 000-fold is achieved, resulting in diagnosis of three major cancers (liver/lung/kidney cancer) with area-under-the-curve of 0.908-0.964 and accuracy of 83.2%-90.6%, which promises a universal detection tool for large-scale clinical diagnosis of human cancers.

摘要

癌症严重威胁人类生命;因此,高精度的诊断对于保护人类免受癌症的折磨至关重要。虽然活检和成像方法是目前癌症诊断中广泛使用的技术,但由于具有快速、简单、经济高效和高身体耐受性的显著优势,预计将出现代谢分析的新型检测平台。然而,分子生物标志物的信号太弱,无法进行高精度诊断。在此,通过精确设计的用于激光解吸/电离质谱的金属有机框架,允许在分子-基底界面内进行有利的电荷转移,并通过调整金属节点的声子散射来减轻热耗散,从而实现了令人惊讶的≈10000 倍的信号增强。由此,实现了对三种主要癌症(肝癌/肺癌/肾癌)的诊断,曲线下面积为 0.908-0.964,准确率为 83.2%-90.6%,有望成为人类癌症大规模临床诊断的通用检测工具。

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