Saranya, Giridharan ; Joseph, Manu M. ; Karunakaran, Varsha ; Nair, Jyothi B. ; Saritha, Valliamma N. ; Veena, Vamadevan S. ; Sujathan, Kunjuraman ; Ajayaghosh, Ayyappanpillai ; Maiti, Kaustabh K. (2018) Enzyme-Driven Switchable Fluorescence-SERS Diagnostic Nanococktail for the Multiplex Detection of Lung Cancer Biomarkers ACS Applied Materials & Interfaces, 10 (45). pp. 38807-38818. ISSN 1944-8244
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Official URL: http://doi.org/10.1021/acsami.8b15583
Related URL: http://dx.doi.org/10.1021/acsami.8b15583
Abstract
Comprehensive profiling of multiple protein targets plays a critical role in the deeper understanding of specific disease conditions associated with high heterogeneity and complexity. Herein, we present the design and fabrication of smart programmable nanoarchitectures, which could integrate clinically relevant diagnostic modalities for the multiplexed detection of most prevalent panel of disease biomarkers present in lung cancer. The multiplex nanoprobes were prepared by attaching dual-functional Raman active fluorogens onto spherical gold nanoparticles through a peptide linker, Phe-Lys-Cys (FKC) which is engineered with a cathepsin B (cathB) enzyme cleavage site. Presence of the cathB induces the scission of FKC upon homing into the cancer cells, resulting in the release of the initially latent fluorophores with a concomitant quenching of the surface enhanced Raman signal intensity, thereby realizing an on-off switching between the fluorescence and Raman modalities. The enzyme triggered switchable nanoprobes were utilized for the simultaneous detection of pathologically relevant lung cancer targets by tethering with specific antibody units. The multiplex-targeted multi-color coded detection capability of the antitags was successfully developed as a valid protein screening methodology which can address the unmet challenges in the conventional clinical scenario for the precise and early diagnosis of lung cancer.
Item Type: | Article |
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Source: | Copyright of this article belongs to American Chemical Society |
ID Code: | 129953 |
Deposited On: | 28 Nov 2022 11:30 |
Last Modified: | 28 Nov 2022 11:30 |
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