Stimuli-Responsive Nanodiamond-Based Biosensor for Enhanced Metastatic Tumor Site Detection. (February 2018)

• Record Type: Journal Article
• Authors: Wang, Xin; Gu, Mengjie; Toh, Tan Boon; Abdullah, Nurrul Lissa Binti; Chow, Edward Kai-Hua
• Is Part Of: SLAS technology. Volume 23:Number 1(2018)
• Page Start: 44
• Page End: 56
• Publication Date: 2018-02
• Subjects: nanomedicine -- metastasis -- diagnostics -- peptide delivery -- cancer; Medical laboratory technology -- Periodicals; Laboratories -- Equipment and supplies -- Periodicals; Diagnosis, Laboratory -- Periodicals; 616.075
• DOI: 10.1177/2472630317735497
• Languages: English
• ISSNs: 2472-6303

Abstract

Metastasis is often critical to cancer progression and linked to poor survival and drug resistance. Early detection of metastasis, as well as identification of metastatic tumor sites, can improve cancer patient survival. Thus, developing technology to improve the detection of cancer metastasis biomarkers can improve both diagnosis and treatment. In this study, we investigated the use of nanodiamonds to develop a stimuli-responsive metastasis detection complex that utilizes matrix metalloproteinase 9 (MMP9) as a metastasis biomarker, as MMP9 increased expression has been shown to be indicative of metastasis. The nanodiamond–MMP9 biosensor complex consists of nanodiamonds functionalized with MMP9-specific fluorescent-labeled substrate peptides. Using this design, protease activity of MMP9 can be accurately measured and correlated to MMP9 expression. The nanodiamond–MMP9 biosensor also demonstrated an enhanced ability to protect the base sensor peptide from nonspecific serum protease cleavage. This enhanced peptide stability, combined with a quantitative stimuli-responsive output function, provides strong evidence for the further development of a nanodiamond–MMP9 biosensor for metastasis site detection. More importantly, this work provides the foundation for use of nanodiamonds as a platform for stimuli-responsive biosensors and theranostic complexes that can be implemented across a wide range of biomedical applications.