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

Coluccio ML, Gentile F, Das G, Nicastri A, Perri AM, Candeloro P, Perozziello G, Proietti Zaccaria R, Gongora JS, Alrasheed S, Fratalocchi A, Limongi T, Cuda G, Di Fabrizio E - Sci Adv (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Bio-Nanotechnology and Engineering for Medicine (BIONEM), Department of Experimental and Clinical Medicine, University of Magna Graecia Viale Europa, Germaneto, Catanzaro 88100, Italy.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Matrix array and data acquisition.(Top left) SEM image of a 10 × 10 SSC array. Scale bar, 2 μm. Each SSC represents a pixel element i,j of the matrix. (Top right) In each pixel, color code is associated with a specific peptide. (Bottom left) A submatrix of 3 × 3 pixels is evidenced. Scale bar, 2 μm. (Bottom right) A detailed SEM image of the SSC representing the pixel. Scale bar, 50 nm. Empty pixels represent specific positions in the array where no peptides are detected.
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Figure 5: Matrix array and data acquisition.(Top left) SEM image of a 10 × 10 SSC array. Scale bar, 2 μm. Each SSC represents a pixel element i,j of the matrix. (Top right) In each pixel, color code is associated with a specific peptide. (Bottom left) A submatrix of 3 × 3 pixels is evidenced. Scale bar, 2 μm. (Bottom right) A detailed SEM image of the SSC representing the pixel. Scale bar, 50 nm. Empty pixels represent specific positions in the array where no peptides are detected.

Mentions: Figure 5 reports additional details explaining SSC code arrays. On the left, a SEM image of the 10 × 10 SSC array is shown (at this magnification, only the overall matrix can be seen). Each pixel (a single SSC) is represented by a color code depicting the linear combination (the fit) of peptides found in that specific pixel. A 10 × 10 matrix is sufficient to fully reconstruct the original peptide mixture.


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

Coluccio ML, Gentile F, Das G, Nicastri A, Perri AM, Candeloro P, Perozziello G, Proietti Zaccaria R, Gongora JS, Alrasheed S, Fratalocchi A, Limongi T, Cuda G, Di Fabrizio E - Sci Adv (2015)

Matrix array and data acquisition.(Top left) SEM image of a 10 × 10 SSC array. Scale bar, 2 μm. Each SSC represents a pixel element i,j of the matrix. (Top right) In each pixel, color code is associated with a specific peptide. (Bottom left) A submatrix of 3 × 3 pixels is evidenced. Scale bar, 2 μm. (Bottom right) A detailed SEM image of the SSC representing the pixel. Scale bar, 50 nm. Empty pixels represent specific positions in the array where no peptides are detected.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643778&req=5

Figure 5: Matrix array and data acquisition.(Top left) SEM image of a 10 × 10 SSC array. Scale bar, 2 μm. Each SSC represents a pixel element i,j of the matrix. (Top right) In each pixel, color code is associated with a specific peptide. (Bottom left) A submatrix of 3 × 3 pixels is evidenced. Scale bar, 2 μm. (Bottom right) A detailed SEM image of the SSC representing the pixel. Scale bar, 50 nm. Empty pixels represent specific positions in the array where no peptides are detected.
Mentions: Figure 5 reports additional details explaining SSC code arrays. On the left, a SEM image of the 10 × 10 SSC array is shown (at this magnification, only the overall matrix can be seen). Each pixel (a single SSC) is represented by a color code depicting the linear combination (the fit) of peptides found in that specific pixel. A 10 × 10 matrix is sufficient to fully reconstruct the original peptide mixture.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Bio-Nanotechnology and Engineering for Medicine (BIONEM), Department of Experimental and Clinical Medicine, University of Magna Graecia Viale Europa, Germaneto, Catanzaro 88100, Italy.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus