Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine

背景(考古学) 精密医学 生物标志物 计算机科学 生物标志物发现 纳米技术 数据科学 计算生物学 医学 材料科学 病理 生物 蛋白质组学 生物化学 基因 古生物学
作者
Javier Plou,Pablo S. Valera,Isabel Garcı́a,Carlos Diego Lima de Albuquerque,Arkaitz Carracedo,Luis M. Liz‐Marzán
出处
期刊:ACS Photonics [American Chemical Society]
卷期号:9 (2): 333-350 被引量:50
标识
DOI:10.1021/acsphotonics.1c01934
摘要

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification of patients based on their predicted disease risk, prognosis, and response to a specific treatment. Up to now, genomics, transcriptomics, and immunohistochemistry have been the main clinically amenable tools at hand for identifying key diagnostic, prognostic, and predictive biomarkers. However, other molecular strategies, including metabolomics, are still in their infancy and require the development of new biomarker detection technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has been recognized as a promising technology for clinical monitoring thanks to its high sensitivity and label-free operation, which should help accelerate the discovery of biomarkers and their corresponding screening in a simpler, faster, and less-expensive manner. Many studies have demonstrated the excellent performance of SERS in biomedical applications. However, such studies have also revealed several variables that should be considered for accurate SERS monitoring, in particular, when the signal is collected from biological sources (tissues, cells or biofluids). This Perspective is aimed at piecing together the puzzle of SERS in biomarker monitoring, with a view on future challenges and implications. We address the most relevant requirements of plasmonic substrates for biomedical applications, as well as the implementation of tools from artificial intelligence or biotechnology to guide the development of highly versatile sensors.
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