The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omicstechnologies have rapidly evolved with the unprecedentedpotential to shape precision medicine. Novel omics approaches areimperative toallow rapid and accurate data collection and integrationwith clinical information and enable a new era of healthcare. Inthis comprehensive review, we highlight the utility of Raman spectroscopy(RS) as an emerging omics technology for clinically relevant applicationsusing clinically significant samples and models. We discuss the useof RS both as a label-free approach for probing the intrinsic metabolitesof biological materials, and as a labeled approach where signal fromRaman reporters conjugated to nanoparticles (NPs) serve as an indirectmeasure for tracking protein biomarkers in vivo andfor high throughout proteomics. We summarize the use of machine learningalgorithms for processing RS data to allow accurate detection andevaluation of treatment response specifically focusing on cancer,cardiac, gastrointestinal, and neurodegenerative diseases. We alsohighlight the integration of RS with established omics approachesfor holistic diagnostic information. Further, we elaborate on metal-freeNPs that leverage the biological Raman-silent region overcoming thechallenges of traditional metal NPs. We conclude the review with anoutlook on future directions that will ultimately allow the adaptationof RS as a clinical approach and revolutionize precision medicine.

Automated summary

With the rapid development of omics technologies, precision medicine is being greatly influenced. Raman spectroscopy (RS) is highlighted as an emerging omics technology for clinically relevant applications. It can be used as a label-free approach to detect intrinsic metabolites and as a labeled approach for tracking protein biomarkers. Machine learning algorithms are utilized for accurate detection of treatment response in diseases like cancer and neurodegenerative diseases. Integration of RS with established omics approaches is also discussed for holistic diagnostic information.