Abstract
Liquid biopsy represents a new frontier of cancer diagnosis and prognosis, which allows the isolation of tumor cells released in the blood stream. The extremely low abundance of these cells needs appropriate methodologies for their identification and enumeration. Herein we present a new protocol based on surface enhanced resonance Raman scattering (SERRS) gold multivalent nanostructures to identify and enumerate tumor cells with epithelial and mesenchimal markers. The validation of the protocol is obtained with spiked samples of peripheral blood mononuclear cells (PBMC). Gold nanostructures are functionalized with SERRS labels and with antibodies to link the tumor cells. Three types of such nanosystems were simultaneously used and the protocol allows obtaining the identification of all individual tumor cells with the help of a Random Forest ensemble learning method.
Highlights
Liquid biopsy represents a new frontier of cancer diagnosis and prognosis, which allows the isolation of tumor cells released in the blood stream
We have already shown that the opportunities given by the surface enhanced resonance Raman scattering (SERRS) approach can be successfully exploited for identifying prostatic tumor cells expressing prostate specific membrane antigen (PSMA) and prostate stem cell antigen (PSCA)[26,31] or other antigens using engineered p eptides[25,34,35]
We address the possibility of identifying and enumerating tumor cells with epithelial and/ or mesenchymal markers, using SERRS multivalent nanostructures and the Random Forest ensemble learning method
Summary
Liquid biopsy represents a new frontier of cancer diagnosis and prognosis, which allows the isolation of tumor cells released in the blood stream. We present a new protocol based on surface enhanced resonance Raman scattering (SERRS) gold multivalent nanostructures to identify and enumerate tumor cells with epithelial and mesenchimal markers. Gold nanostructures are functionalized with SERRS labels and with antibodies to link the tumor cells Three types of such nanosystems were simultaneously used and the protocol allows obtaining the identification of all individual tumor cells with the help of a Random Forest ensemble learning method. The functionalization of plasmonic nanostructures with a large number of antibodies (Abs) increases the targeting activity with respect to isolated A bs[36,37] This interesting possibility can be exploited using different types of Abs on the same nanostructure, which allows to further increase its a vidity[38]
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