## 4 Discussion  
The staging of breast cancer is made according to the TNM system, which takes into account the size of the tumour (T), the presence of metastases in the lymph nodes (N) and on the presence of distant metastases (M) [5]. If a distant metastasis is present, the disease is considered stage IV irrespective of the size of the tumour and the presence of metastases in the lymph nodes. Among the 53 patients in the breast cancer group, stage I disease was present in 5% of patients, stage II was present in around 40% of the patients while 55% of the patients had stage III breast cancer (Figure 1). No patient had stage IV disease, which means that all patients were free of distant metastases. The bias towards stage II and III cases was determined by the fact that sample collection was performed in a tertiary referral hospital specialized in breast cancer surgery. Thus, only few cases with stage I breast cancer were referred to the clinic in which patient enrolment took place. The lack of stage IV breast cancer is explained by the fact that these cases are usually treated only with chemotherapy and/or radiotherapy. For the acquisition of high-intensity SERS spectra from urine, we employed hya-AgNPs which were SERS-activated using Ca\({}^{2+}\). The SERS signature of the urine samples suggests that the main class of metabolites to chemisorb onto the metal surface is represented by purine metabolites [18; 24]. We have recently showed that cations such as Ca\({}^{2+}\) or Mg\({}^{2+}\) facilitate the specific adsorption of anionic species, including citrate and chloride ions, which chemisorb onto the nanoparticles in the order of their relative affinity for the activated metal surface [19; 22]. Moreover, the SERS activating effect does not depend on the aggregation of the nanoparticles, as evidenced by the absence of a measurable shift  
Figure 5: The principal component analysis - linear discriminant analysis (PCA-LDA) model yielded by SERS spectra acquired from the urine samples of patients with breast cancer (n = 53) and controls (n = 22). The discriminant values of the PCA-LDA model (**a**). The corresponding confusion matrix of the PCA-LDA model (**b**). in the plasmon resonance after the addition of Ca\({}^{2+}\) 10\({}^{-4}\) M (Figure 2). The absence of a shift in the absorbance maximum also explains the use of the 532 nm laser in favour of other laser lines such as the 633 nm or 785 nm lines due to (pre)resonant conditions with the surface plasmons of nanoparticles (UV-Vis absorption maximum at 408 nm). Using the 532 nm laser is also convenient because the sensitivity of the detector and the transmittance of the optical components of the spectroscopy are maximal for this laser line. When acquiring SERS spectra from purine metabolites using a colloid such as hya-AgNPs that contains chloride ions from the synthesis reaction, there is a competitive adsorption to the AgNPs surface between chloride ions and purine metabolites that favours the later due to their higher affinity for the silver surface. The addition of Ca\({}^{2+}\) or Mg\({}^{2+}\) shifts the equilibrium towards purine metabolites even further, leading to an increase in the SERS intensity of purine metabolites such as uric acid (Figure S1). In contrast to the study by [PERSON] et al. [11], which filtered the urine using centrifugal filter devices for eliminating proteins, our strategy allowed the acquisition of intense SERS spectra of purine metabolites without any filtering step, since the Ca\({}^{2+}\) added to the solution facilitated the specific adsorption of purine metabolites to the detriment of proteins traces [19; 22]. Conversely, the chemisorption of proteins can also be favoured in the detriment of purine metabolites by modifying the nanoparticles with iodide, as shown recently in our study regarding albumin detection in urine [22]. It is worth mentioning that this strategy works well only for biofluids containing low concentrations of proteins such as urine [22].