Label-free serum ribonucleic acid analysis for colorectal cancer detection by surface-enhanced Raman spectroscopy and multivariate analysis

• Published in: Journal of Biomedical Optics 2012-06, Vol.17 (6), p.067003-1-067003-2
• Main Authors: Chen, Yanping, Chen, Gang, Feng, Shangyuan, Pan, Jianji, Zheng, Xiongwei, Su, Ying, Chen, Yan, Huang, Zufang, Lin, Xiaoqian, Lan, Fenghua, Chen, Rong, Zeng, Haishan
• Format: Article
• Language: English
• Subjects: 3-D Ag nanofilm; Aged; Cancer; cancer screening; Case-Control Studies; circulating nucleic acids; colorectal cancer; Colorectal Neoplasms - pathology; Early Detection of Cancer - methods; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Humans; Linear Models; Metal Nanoparticles - chemistry; Microscopy, Confocal - methods; Microscopy, Electron, Scanning - methods; Middle Aged; Multivariate Analysis; Nanostructure; Principal Component Analysis; Raman scattering; Ribonucleic acids; RNA - blood; RNA - metabolism; Sensitivity and Specificity; Serums; Silver; Silver - chemistry; Spectral lines; Spectrum Analysis, Raman - methods; Surface Properties; surface-enhanced Raman scattering; Three dimensional
• ISSN: 1083-3668; 1560-2281
• DOI: 10.1117/1.JBO.17.6.067003

Studies with circulating ribonucleic acid (RNA) not only provide new targets for cancer detection, but also open up the possibility of noninvasive gene expression profiling for cancer. In this paper, we developed a surface-enhanced Raman scattering (SERS), platform for detection and differentiation of serum RNAs of colorectal cancer. A novel three-dimensional (3-D), Ag nanofilm formed by dry aggregated silver nanoparticles, Ag NP, as the SERS-active substrate was presented to effectively enhance the RNA Raman signals. SERS measurements were performed on two groups of serum RNA samples. One group from patients, with pathologically diagnosed colorectal cancer and the other group from healthy controls, . Tentative assignments of the Raman bands in the normalized SERS spectra demonstrated that there are differential expressions of cancer-related RNAs between the two groups. Linear discriminate analysis, based on principal component analysis, generated features can differentiate the colorectal cancer SERS spectra from normal SERS spectra with sensitivity of 89.1 percent and specificity of 95.6 percent. This exploratory study demonstrated great potential for developing serum RNA SERS analysis into a useful clinical tool for label-free, noninvasive screening and detection of colorectal cancers.