文献类型：期刊文献

英文题名：Specific Screening of Prostate Cancer Individuals Using an Enzyme-Assisted Substrate Sensing Platform Based on Hierarchical MOFs with Tunable Mesopore Size

作者：Zhao, Liwei[1];Yang, Jian[1];Gong, Ming[1];Li, Ke[1];Gu, Jinlou[1]

机构：[1]East China Univ Sci & Technol, Sch Mat Sci & Engn, Key Lab Ultrafine Mat, Minist Educ, Shanghai 200237, Peoples R China

年份：2021

卷号：143

期号：37

起止页码：15145

外文期刊名：JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

收录：;EI(收录号：20213910949398);WOS:【SCI-EXPANDED(收录号:WOS:000700883200027)】；

基金：This work was financially supported by the Natural Science Foundation of China (21975072, 51902106) and the Natural Science Foundation of Shanghai (18ZR1408700).

语种：英文

外文关键词：Biomarkers - Diseases - Diagnosis - Urology - Enzymes - Metal-Organic Frameworks

摘要：Rapid and specific identification of tumor metabolic markers is of great significance. Herein, a convenient, reliable and specific strategy was proposed to screen prostate cancer (PCa) individuals through indirectly quantifying sarcosine, an early indicator of PCa, in the clinical urine samples. The success roots in the rational design of a cascade response model, which takes integrated sarcosine oxidase (SOX) as a specific recognition unit and oxygen-sensitive molecule as a signal reporter. The newly developed hierarchical mesoporous Zr-based metal- organic frameworks with continuously tunable mesopore size ensure the synergetic work of the SOX and response unit spatially separated in their neighboring mesoporous and microporous domains, respectively. The large mesopore up to 12.1 nm not only greatly enhances the loading capacity of SOX but also spares enough space for the free diffusion of sarcosine. On this basis, the probe is competent to specifically check out the tiny concentration change of sarcosine in the urine sample between PCa patients and healthy humans. Such a concept of enzyme-assisted substrate sensing could be simply extended by altering the type of immobilized enzymes, hopefully setting a guideline for the rational design of multiple probes to quantify specific biomarkers in complex biological samples.