e1500487.full.pdf (1.64 MB)
Detection of single amino acid mutation in human breast cancer by disordered plasmonic self-similar chain
journal contribution
posted on 2023-06-09, 07:33 authored by Maria Laura Coluccio, Francesco Gentile, Gobind Das, Annalisa Nicastri, Angela Mena Perri, Patrizio Candeloro, Gerardo Perozziello, Remo Proietti Zaccaria, Juan Sebastian Totero Gongora, Salma Alrasheed, Andrea Fratalocchi, Tania Limongi, Giovanni Cuda, Enzo Di FabrizioControl of the architecture and electromagnetic behavior of nanostructures offers the possibility of designing and fabricating sensors that, owing to their intrinsic behavior, provide solutions to new problems in various fields. We show detection of peptides in multicomponent mixtures derived from human samples for early diagnosis of breast cancer. The architecture of sensors is based on a matrix array where pixels constitute a plasmonic device showing a strong electric field enhancement localized in an area of a few square nanometers. The method allows detection of single point mutations in peptides composing the BRCA1 protein. The sensitivity demonstrated falls in the picomolar (10-12 M) range. The success of this approach is a result of accurate design and fabrication control. The residual roughness introduced by fabrication was taken into account in optical modeling and was a further contributing factor in plasmon localization, increasing the sensitivity and selectivity of the sensors. This methodology developed for breast cancer detection can be considered a general strategy that is applicable to various pathologies and other chemical analytical cases where complex mixtures have to be resolved in their constitutive components.
History
Publication status
- Published
File Version
- Published version
Journal
Science AdvancesISSN
2375-2548Publisher
American Association for the Advancement of ScienceExternal DOI
Issue
8Volume
1Article number
e1500487Department affiliated with
- Physics and Astronomy Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2017-11-15First Open Access (FOA) Date
2017-11-15First Compliant Deposit (FCD) Date
2017-11-15Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC