Label-free distinction between p53+/+ and p53-/- colon cancer cells using a graphene based SERS platform

被引:25
作者
Liang, Owen [1 ,3 ,4 ]
Wang, Pu [1 ]
Xia, Ming [1 ]
Augello, Catherine [2 ]
Yang, Fan [1 ]
Niu, Gang [3 ,4 ]
Liu, Huinan [2 ,5 ,6 ]
Xie, Ya-Hong [1 ,3 ,4 ,7 ]
机构
[1] Univ Calif Los Angeles, Dept Mat Sci & Engn, Los Angeles, CA 90095 USA
[2] Univ Calif Riverside, Dept Bioengn, Riverside, CA 92521 USA
[3] Xi An Jiao Tong Univ, Minist Educ, Key Lab, Elect Mat Res Lab, Xian 710049, Shaanxi, Peoples R China
[4] Xi An Jiao Tong Univ, Sch Elect & Informat Engn, Int Ctr Dielect Res, Xian 710049, Shaanxi, Peoples R China
[5] Univ Calif Riverside, Sch Med, Cell Mol & Dev Biol CMDB Program, Riverside, CA 92507 USA
[6] Univ Calif Riverside, Sch Med, Biomed Sci Program, Riverside, CA 92507 USA
[7] Univ Calif Los Angeles, Jonsson Comprehens Canc Ctr, Los Angeles, CA 90024 USA
关键词
Graphene; SERS; Colon; Cancer; Label-Free; p53; ENHANCED RAMAN-SCATTERING; SPECTROSCOPY SERS; SURFACE PROTEOME; TISSUES;
D O I
10.1016/j.bios.2018.07.038
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Surface-Enhanced Raman Scattering (SERS) is used to differentiate two colon cancer cell line HCT 116, that is, to distinguish a TP53 gene knockout cell line (p53 -/-) from a wild type (p53 +/+). A label-free graphene/gold nanopyramid based SERS platform, combined with the multivariate analysis: principal component analysis, is used to profile live, dead, and burst colon cancer cells suspended in simulated body fluid (SBF). The graphene sheet permits SERS hotspot identification and provides a chemical enhancement for the biological constituents. This study found that a unique fingerprint exists for three different states of the cell, burst, live, and dead, which were used to differentiate the p53 +/+ and p53 -/- cell lines. Perceptron with Pocket Algorithm was also coupled with PCA to demonstrate an average of 81% sensitivity and 97% specificity in separating the two cell lines. The demonstration of single gene differentiation shows the great applicable potential of this SERS graphene hybrid platform for cancer diagnosis.
引用
收藏
页码:108 / 114
页数:7
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