Advances in Protein Biomarker Assay via the Combination of Molecular Imprinting and Surface-enhanced Raman Scattering

Abstract

Abnormal protein expression closely correlates with the occurrence and development of diseases. Thus, proteins have been widely used as disease markers for early diagnosis, treatment monitoring and prognosis evaluation of diseases. However, protein biomarkers in clinical samples are usually present in extremely low concentration while the detection often suffers from severe interference by high-abundance sample matrix, which challenges the specificity and sensitivity of protein biomarker assay methods. Currently, the main detection method of protein biomarkers is immunoassay. Nevertheless, immunoassay mainly relies on antibodies for specific recognition, and antibodies are associated with disadvantages such as difficulty in preparation, poor stability, and high-cost. Meanwhile, immunoassay is mainly based on fluorescence and chemiluminescence to achieve high-sensitivity detection, but they have inherent defects such as cumbersome operation, photobleaching and broad spectrum. Molecularly imprinted polymers (MIP) have developed as biomimetic recognition materials with antibody-comparable specificity and affinity, while offering advantages such as ease in preparation, good stability and low cost. On the other hand, surface-enhanced Raman scattering (SERS) has been widely used in chemical or biological assays due to its merits including ultra-high sensitivity, narrow spectrum, speed, non-destructivity, and so on. In recent years, the combination of molecular imprinting and SERS has generated a series of advanced protein detection methods that exhibited unique strengths, which has gained wide attention. This review aims to survey the main advances of this hybrid analytical technique. After introduction of MIP and SERS as well as their separate applications in the detection of protein biomarkers, we mainly focus on the combination of MIP and SERS as well as its application in protein biomarker detection. We finally briefly sketch the future development of this hybrid analytical method.