## 2 The Label-Free Approach  
The label-free approach is one of major strategies for the detection of biomolecules using the SERS method. Since in the label-free approach a molecule of interest directly interacts with a SERS sensor, the SERS signal comes from the reporter molecule. This provides reliable spectral information about the molecular structure of the analyte without uncertainties due to the labeling of the sensors used in indirect strategy. Using the label-free approach makes it possible to identify the analyte in a complex mixture without a separation step or functionalization of a sensor. In this section, the latest achievements in the identification and analysis of exosome-like vesicles using non-functionalized SERS substrates are discussed. For the convenience of the readers, we have summarized these in Table 1.  
[PERSON] et al. showed a novel approach to identifying single exosome-like vesicles (ELVs) derived from red blood cells (RBC) and B16F10 melanoma cancer cells using the SERS method. The diagnostic approach is based on the electrostatic adsorption of cationic gold nanoparticles (AuNP) onto the anionic surface of ELVs, resulting in AuNP coating around ELVs. To obtain a colloidally stable suspension of AuNP coated ELVs, the optimal AuNP numbers were determined to be 600 AuNP per B16F10 vesicle and 1200 AuNP per RBC vesicle, respectively. SERS spectra of individual ELVs with a high density of AuNP were then acquired along with performing spectral analyses of the obtained Raman spectra by applying two statistical models. Furthermore, the authors were able to discriminate between AuNP coated B16F10 cancerous and RBC-derived ELVs upon mixture at two different ratios, which simulates the in vivo situation. The method appears promising for detecting cancerous ELVs in complex mixtures containing different types of vesicles simultaneously. Although there were some variations in the SERS spectra of individual ELVs, the developed approach is very simple and can be integrated with standard methods, for example, microfluidics enabling automated and rapid SERS diagnostics [94]. The label-free analysis of exosomes derived from the SKOV3 cell line was performed using SERS-active 3D nanobowls by trapping the exosomes into multiple and individual SERS-active 3D nanobowls [95]. Nanobowl-based SERS substrates, illustrated in Figure 1a, provide more reproducible SERS intensities when compared to the nanoparticle-based approaches due to a more uniform \"hot-spots\" density. Very few exosomes can be trapped into a single nanobowl, which enables the analysis of few particles. As the exosomes stay inside the nanobowls and are intact due to a solution inside the bowls, the SERS signals were exclusively originated from the solution kit used to isolate the exosome. The enhancement is greatest within 5 nm from the nanobowl surface, which corresponds to the lipid membrane thickness and thus allows SERS signals only from the exosome surface. The changes in SERS spectra were observed due to the release of exosomal contents on the bowl surface as a result of exosome damage during drying of the samples. Principal component analysis (PCA) of time-dependent SERS measurements and SERS spectra obtained from ultracentrifugation purified exosomes confirmed the interaction of exosome cargo with the bowl surface. The biochemical composition of normal and lung cancer exosomes was examined by utilizing a hot-spot originating between well-aligned gold nanorods (AuNR) and silver nanocubes (AgNC) as demonstrated in Figure 1b [96]. The optimized SERS substrates have shown the possibility of detecting the exosomes at concentrations \(10^{4}\)-\(10^{5}\) times lower than the normal blood amount. The peaks of proteins, nucleic acids, and lipids were dominated in the SERS spectra of normal lung exosomes, whereas the contributions from proteins were observed in the SERS spectra of lung cancer exosomes. The spectral differences were also found between the exosomes derived from fibroblast and epithelium cell lines.