## 3 Results  
In this study, we acquired SERS spectra of urine samples from n = 53 breast cancer patients and n = 22 controls. The distribution of patients according to stage I, II and III breast cancer is presented in Figure 1. The average age of the breast cancer patients was 55 \(\pm\) 11 years, while the average age of the control group was 45 \(\pm\) 5 years. The detailed information regarding stage and age for each patient is presented in Table S1. Adding cations such as Ca\({}^{2+}\) or Mg\({}^{2+}\) to the silver colloid promotes the chemisorption of anionic species (including purine metabolites) to the silver surface and the switching on of the SERS effect, without necessarily aggregating the nanoparticles, as shown recently by us [19; 22]. For instance, adding Ca\({}^{2+}\) 10\({}^{-4}\) M leads to intense SERS spectra of uric acid 10\({}^{-4}\) M, while in the absence of Ca\({}^{2+}\), the spectra are much weaker (Figure S1 in the Supplementary Materials). No aggregation of the hya-AgNPs was observed by the addition of Ca\({}^{2+}\) up to 10\({}^{-4}\) M. To test the stability of the hya-AgNPs after their supplementary activation with Ca\({}^{2+}\) up to 10\({}^{-4}\) M, we acquired UV-Vis absorption spectra of nanoparticles before and after activation with Ca\({}^{2+}\) 10\({}^{-4}\) M. The UV-Vis spectrum of hya-AgNPs showed the characteristic plasmonic resonance band at 408 nm (Figure 2), which did not suffer any significant shift after the SERS-activation of the colloid. Thus, the results showed an overlap in the UV-Vis spectra between the two time points. For the acquisition of the SERS spectra, we employed the 532 nm laser (green), which meets pre-resonant conditions with the absorption maximum of the nanoparticles. The average SERS spectra of urine samples from breast cancer patients and controls along with the difference spectrum are  
Figure 1: Distribution of breast cancer patients with stage I, II and III disease. Figure 2: Mean UV-Vis spectra of as synthesized hya-AgNPs and after the addition of Ca(NO\({}_{3}\))\({}_{2}\) 10\({}^{-4}\) M to the hya-AgNPs. The standard deviation is represented by the shaded area. presented in Figure 3. The standard deviation of the difference spectrum, which is a measure of the robustness of the separation between the groups, is presented as a grey shaded area  
The SERS spectra in Figure 3 are dominated by several bands tentatively attributed to uric acid at 650, 809, 1017, 1135 and 1522 cm\({}^{-1}\). The SERS bands tentatively attributed to xanthine are represented by the ones at 1135, 1251 and 1318 cm\({}^{-1}\) while the bands at 724, 1094, 1459 and 1595 cm\({}^{-1}\) were tentatively attributed to hypoxanthine [18; 23; 24]. However, several bands remained unassigned. To explore the spectral data which has a significant variability across SERS spectra, we performed PCA (Figure 4). Figure 4a depicts the grouping of samples based on the score values of PC 1 and PC 3, which performed best in separating the two groups. Figure 4b shows the corresponding loading plots of PC 1 and PC 3, which depict the SERS bands captured by each PC. Given that PCA is an unsupervised statistical method, some bands are present across PCs. Figure 4: Principal component analysis of SERS acquired from patients with breast cancer (n = 53) and controls (n = 22). Score plot showing the separation of samples based on principal component (PC) 1 and PC 3 (**a**). Loading plots corresponding to PC 1 and PC 3 depicting SERS bands attributed mainly to uric acid, xanthine and hypoxanthine (**b**). Figure 3: Average surface-enhanced Raman scattering (SERS) spectra of urine samples from breast cancer patient (n = 53) and controls (n = 22) and the difference spectrum. Shaded area represents standard deviation. To test the classification accuracy yielded by SERS spectra of urine, we also performed PCA-LDA, using the first 7 PCs as input, which captured 82% of the variability of the original data set (Figure S2). The discriminant values of PCA-LDA are presented in Figure 5a.