401
Chapter 14
Quantitative Analysis of Disease Biomarkers
Using Surface-Enhanced Raman Scattering
Spectroscopy
Hyangah Chon and Jaebum Choo
m. Baranska (ed.), Optical Spectroscopy and Computational Methods in Biology and
Medicine, Challenges and Advances in Computational Chemistry and Physics 14,
doI 10.1007/978-94-007-7832-0_14, © Springer Science+Business media dordrecht 2014
J. Choo ()
department of Bionano Engineering and Center for Integrated human Sensing System,
hanyang university, Ansan 426-791, Korea
e-mail: jbchoo@hanyang.ac.kr
h. Chon
department of Bionano Engineering, hanyang university, Ansan 426-791, Korea
e-mail: hyangahchon@gmail.com
Abstract In this chapter, we describe the SERS-based immunoassay technique for
the highly sensitive detection of various disease biomarkers. the fundamentals of
the technique are briefly presented, and three different SERS assay platforms and
their biomedical applications are described. the novel SERS-based assay technique
is expected to be a powerful clinical tool for early disease diagnosis.
Keywords Surface-enhanced Raman scattering (SERS) • Immunoassay • Biomarker • Early diagnosis • Microfluidics
14.1 Introduction
Immunoassays are a fast and cost-effective method that can be applied to biochemical studies, clinical diagnostics, food safety tests and environmental monitoring
[1–3]. Enzyme-linked immunosorbent assay (ELISA) is the most widely used
screening tool for validating candidate protein markers [4]. this technique allows
for the simultaneous estimation of the concentration of numerous biomarkers in a
small volume. ELISAs also have several significant advantages over other conventional assay methods, such as a high-throughput performance, cost-effectiveness
and facile clinical applications. Nonetheless, this assay technique has some technical limitations. Fluorescence detection using molecular labels is commonly used
to identify a specific antigen-antibody interaction in an immunoassay; however,
this has several drawbacks including a poor limit of detection, photobleaching, and
limited multiplex detection capability [5–7].
Chapter 14
Quantitative Analysis of Disease Biomarkers
Using Surface-Enhanced Raman Scattering
Spectroscopy
Hyangah Chon and Jaebum Choo
m. Baranska (ed.), Optical Spectroscopy and Computational Methods in Biology and
Medicine, Challenges and Advances in Computational Chemistry and Physics 14,
doI 10.1007/978-94-007-7832-0_14, © Springer Science+Business media dordrecht 2014
J. Choo ()
department of Bionano Engineering and Center for Integrated human Sensing System,
hanyang university, Ansan 426-791, Korea
e-mail: jbchoo@hanyang.ac.kr
h. Chon
department of Bionano Engineering, hanyang university, Ansan 426-791, Korea
e-mail: hyangahchon@gmail.com
Abstract In this chapter, we describe the SERS-based immunoassay technique for
the highly sensitive detection of various disease biomarkers. the fundamentals of
the technique are briefly presented, and three different SERS assay platforms and
their biomedical applications are described. the novel SERS-based assay technique
is expected to be a powerful clinical tool for early disease diagnosis.
Keywords Surface-enhanced Raman scattering (SERS) • Immunoassay • Biomarker • Early diagnosis • Microfluidics
14.1 Introduction
Immunoassays are a fast and cost-effective method that can be applied to biochemical studies, clinical diagnostics, food safety tests and environmental monitoring
[1–3]. Enzyme-linked immunosorbent assay (ELISA) is the most widely used
screening tool for validating candidate protein markers [4]. this technique allows
for the simultaneous estimation of the concentration of numerous biomarkers in a
small volume. ELISAs also have several significant advantages over other conventional assay methods, such as a high-throughput performance, cost-effectiveness
and facile clinical applications. Nonetheless, this assay technique has some technical limitations. Fluorescence detection using molecular labels is commonly used
to identify a specific antigen-antibody interaction in an immunoassay; however,
this has several drawbacks including a poor limit of detection, photobleaching, and
limited multiplex detection capability [5–7].