Frontiers in Raman nano-diagnostics: SERS and TERS of extracellular vesicles for cancer detection

Efforts to create rapid, non-invasive, and reliable cancer diagnostics have increasingly focused on extracellular vesicles (EVs), nanoscale carriers of proteins, lipids, and nucleic acids that mirror the molecular state of their parent cells and mediate communication within the tumor microenvironment. Their complex composition and heterogeneity present however, significant challenges for analytical characterization. Raman spectroscopy, with its ability to probe molecular vibrations, has emerged as a possible technique for EV analysis. In this review, we highlight recent advances in Raman-based techniques, including conventional Raman, surface-enhanced Raman spectroscopy (SERS), tip-enhanced Raman spectroscopy (TERS), and emerging hybrid modalities where nanomaterials serve as critical platforms to amplify signals and resolve EV heterogeneity. We discuss how engineered nanostructures enable sensitive detection, molecular fingerprinting, and spatially resolved characterization of EVs. Integration with machine learning data analytics approaches further enhances classification accuracy across healthy, benign, and malignant samples, improving the accuracy and reliability of the spectroscopic investigation. Finally, we discuss translational prospects, including AFM-IR technologies that appear particularly well suited to the analysis of single EVs, enabling interrogation of both surface chemistry and internal cargo owing to the greater penetration depth of infrared radiation. In parallel, microfluidic platforms offer powerful solutions for the controlled delivery, sorting, and trapping of EVs within optical microscopy configurations. Collectively, the continued development and integration of these non-invasive analytical tools hold substantial promise for EV-based cancer diagnostics and open new avenues for biomarker discovery.