Detection of single amino acid mutation in human breast cancer by disordered plasmonic self-similar chain.

Sci Adv 2015 Sep 4;1(8):e1500487. Epub 2015 Sep 4.

Bio-Nanotechnology and Engineering for Medicine (BIONEM), Department of Experimental and Clinical Medicine, University of Magna Graecia Viale Europa, Germaneto, Catanzaro 88100, Italy. ; Physical Sciences and Engineering (PSE) and Biological and Environment Science and Engineering Divisions (BESE), King Abdullah University of Science and Technology, Thuwal 23955-6900, Kingdom of Saudi Arabia.

Control 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.

Download full-text PDF

Source
http://dx.doi.org/10.1126/sciadv.1500487DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4643778PMC
September 2015
41 Reads

Publication Analysis

Top Keywords

breast cancer
12
detection single
8
electric field
4
sensitivity selectivity
4
selectivity sensors
4
strong electric
4
sensors methodology
4
showing strong
4
field enhancement
4
increasing sensitivity
4
detection
4
square nanometers
4
nanometers method
4
area square
4
localization increasing
4
device showing
4
localized area
4
enhancement localized
4
methodology developed
4
architecture sensors
4

Similar Publications