# Enhancing Disease Diagnosis: Biomedical Applications of Surface-Enhanced Raman Scattering
## 5 Applications of SERS in Disease Diagnostics
### SERS in Breath Analysis  
Breathomics is defined as the metabolomics of exhaled air. Human exhaled breath predominantly consists of water, oxygen, nitrogen, nitric oxide and carbon dioxide. In addition, it contains thousands of small gaseous volatile organic compounds (VOCs) which are produced by numerous and highly regulated metabolic reactions in various metabolic pathways [133]. Since the structural identity and abundance of endogenous VOCs vary depending on the health status of an individual, the field of breathomics has much potential as a powerful noninvasive platform for biomarker discovery. Moreover, since each patient produces unique characteristic VOC signatures for specific illnesses, breathomics will potentially play a crucial role in personalised medicine [134]. Despite attracting increasing attention, the progress of breathomics research for clinical diagnostics is relatively slow partly due to limitations associated with capture of breath, and selective and sensitive detection of trace quantities of VOCs [135]. Electronic nose (eNose) technology is an emerging portable tool for pattern recognition in composite responses of mixed VOCs (breathprint). Although eNose provides breathprints that can be used to detect asthma and chronic obstructive pulmonary disease (COPD) [136], it does not identify individual VOC markers within a complex mixture. Ion mobility spectrometry (IMS) is a relatively sensitive method though it is destructive, may not be ideal for complex VOC mixtures and its long term reproducibility is yet to be demonstrated [137]. Currently, GC-MS is the gold standard for global profiling of exhaled VOCs related to abnormal metabolism and extrapolated to cancers, diabetes etc. However, if the goal is to develop a rapid analytical tool for online diagnostics and/or offline use in real-time at the PoC especially in low income countries, then GC-MS is perhaps not convenient. In addition as partly stated earlier, GC-MS requires professional operators, lengthy procedures, and high instrument maintenance and consumables costs. This is where SERS prevails in clinical practice to offer low-cost but quicker detection of disease-specific singular or multiplex VOC targets directly in exhaled breath at a point of need. The fact that both exogenous and endogenous VOCs are present at trace concentrations in exhaled breath; SERS is an exciting prospect as it may allow for the detection of any VOCs adsorbed onto nanomaterials, down to single-molecule level [138]. Although SERS as a clinical diagnostic tool for breath analysis is currently at the budding stage, the results obtained so far shows unprecedented potential. Initial proof-of-concept work aimed to detect low amounts of pure acetone and ethanol vapour at LODs of 3.7 pg and 1.7 pg, respectively, as singular or duplex markers of glucose level in plasma [139; 140]. Nevertheless, due to complex pathogenesis associated with breath-related infections, where multiple biochemical and cellular processes are linked to innate and adaptive mechanisms, human exhaled breath is chemically complex. Hence, VOC components should be'sorted out' to improve pathophysiological assessment of various diseases. An interesting study by [PERSON] et al. was initially applied a high-throughput GC-MS, to capture this biological complexity, and SERS in parallel, to discriminate between early and advanced gastric cancer (EGC and AGC respectively) from healthy controls [141]. Using GC-MS and solid phase microextraction, 14 characteristic volatile metabolites were screened and identified in human exhaled breath. SERS based on in situ synthesised AuNPs coated on graphene oxide then detected individual profiles for all 14 VOCs rapidly and accurately in both simulated and real exhaled breath sampled from patients of gastric cancer. PCA scores plot of SERS successfully discriminated healthy, EGC and AGC in 200 breath samples at diagnostic sensitivity of >92% and specificity of >83%, very comparable to that of GC-MS, though quantitative characterisation was not demonstrated [141].