Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/43069
Title: Surface enhanced Raman spectroscopy based immunosensor for ultrasensitive and selective detection of wild type p53 and mutant p53R175H
Authors: Anna Rita Bizzarri
Moscetti, Ilaria
Cannistraro, Salvatore 
Journal: ANALYTICA CHIMICA ACTA 
Issue Date: 2018
Abstract: 
p53 is a powerful transcription factor playing a pivotal role in the prevention of cancer development and in maintaining genome integrity. This oncosuppressor is found to be functionally inactivated by mutations in many human tumors. Accordingly, wild type p53 and its oncogenic mutants represent valuable cancer biomarkers for diagnostic and prognostic purposes. We developed a highly sensitive biosensor, based on Surface Enhanced Raman Spectroscopy, for detection of wild type p53 and of p53R175H, which is one of the most frequent tumor-associated mutants of p53. Our approach combines the huge Raman signal enhancement, mainly arising from the plasmonic resonance effect on molecules close to gold nanoparticles, with the antigen-antibody biorecognition specificity. By following the enhanced signal of a specific Raman marker, intrinsic to the nanoparticle-antibody bioconjugation, we were able to push the antigen detection level down to the attomolar range in buffer and to the femtomolar range in spiked human serum. The method demonstrated a high reproducibility and a remarkable selectivity in discriminating between wild type p53 and p53R175H mutant, in both buffer and serum. A calibration plot was built and validated by ELISA for a reliable quantification of p53. These findings entitle our SERS-based immunosensor as a powerful and reliable tool for a non-invasive screening in human serum targeting p53 network. The approach could be easily extended to ultrasensitive detection of other markers of general interest, with feasible implementations into multiplex assays, functioning as lab-on-chip devices for several applications.
URI: http://hdl.handle.net/2067/43069
ISSN: 0003-2670
DOI: 10.1016/j.aca.2018.04.049
Appears in Collections:A1. Articolo in rivista

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