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

Abstract

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.

Expanding the Multiplexing Capabilities of Raman Imaging to Reveal Highly Specific Molecular Expression and Enable Spatial Profiling

“…However, for some techniques, spectra are notoriously difficult to extensively multiplex, while others are laborious, are destructive to the sample, , and can even lack protein specificity. Raman spectral imaging is perfectly suited to perform molecular imaging without suffering from these limitations. − Molecular imaging of biological samples stained with various batches of SERS NP contrast agents, which we call SERS flavors, leverages the chemical specificity of Raman spectroscopy to transmit the state of biomarker expression in the form of multiplexed Raman spectroscopic optical signals. , The enhancement factor of the scattering cross-section achieved by localized surface plasmon resonance (LSPR) of nanoscale gold affords high sensitivity and fast mapping speeds using nondestructive laser intensities . As a result, the Raman spectrum of each SERS flavor can serve as a unique barcode for discovering and localizing a multitude of protein targets simultaneously. − Previously, the largest reported number of SERS NPs multiplexed during Raman imaging was achieved with 10 unique SERS flavors .…”

Malaria Diagnostics

“…Although their application is still in its infancy, it will solve a lot of challenges. Machine learning algorithms could improve SERS data processing for example through calibration multicomponent samples and the identification of interferences in complex biochemical samples, identifying SERS hotspots and analysing complex SERS spectra [23]. Irreproducibility of the SERS substrate is the bottleneck for their commercialisation or clinical application.…”

Materials Perspectives of Integrated Plasmonic Biosensors

“…The role of artificial intelligence will increase in future plasmonic biosensors for analyzing complex sensor data [ 217 ], reducing signal interference [ 218 ], removing of noisy signals [ 218 ], and high-throughput screening [ 219 ]. We propose the following ideas as future research directions for plasmonic biosensors: Enhance the adhesion between plasmonic nanoparticles and flexible substrates; either using new polymer material substrates or by controlling the synthesis process.…”