## 2 Results
### Untargeted Metabolomics Analysis  
The attained data was subjected to principal component analysis (PCA) in order to assess data quality as well as determine differences between the metabolic profiles of control and BC patients. As shown in Figure 1A,B, QC samples formed a tight cluster, confirming the quality of the obtained results. Additionally, the two studied groups achieved relatively good separation in both positive and negative ionization modes. Based on the PCA score plots and a 95% confidence ellipse using Hotelling T-squared, five outliers were removed: three from the group of BC patients and two from the healthy group for positive ionization mode, and two from the group of BC patients and three from the healthy group for negative ionization mode. Thereafter, supervised multivariate analysis: orthogonal projections to latent structures discriminant analysis (OPLS-DA) was performed to achieve maximum separation among the groups (Figure 1C,D). The Q2 and R2 values for the model were 46% and 85.2% for positive ionization mode and 43.3% and 88.2% for negative ionization mode, respectively. Based on the obtained model, metabolites found to contribute the most in differentiating the two groups according to their VIP scores were selected for further analysis. A VIP score value >1 was selected as cut-off value. Table 2 shows the metabolites meeting the abovementioned criteria. Additional information regarding the annotation of these compounds is presented in Supplementary Information Table S1. Figure 2 presents Box Whisker plots for selected annotated metabolites exhibiting significant differences in urinary levels between BC patients and healthy controls. Chromatograms for each of these compounds are shown in Supplementary Information Figure S2. Box Whisker plots represent peak areas for a selected component on the y axis as a rectangle against equally spaced sample groups on the x axis. The height of the rectangle represents the peak areas in the interquartile range. The following equations were used to calculate the upper and lower whiskers: Interquartile range (IQR) = Quartile 3 (Q3) - Quartile 1 (Q1), Upper whisker = Q3 + IQR \(\times\) 1.5, Lower whisker = Q1 - IQR \(\times\) 1.5. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Studied Group**} & \multicolumn{2}{c}{**Group Size**} & \multirow{2}{*}{**Age [years]**} & \multirow{2}{*}{**BMI [kg/m\({}^{2}\)]**} & \multirow{2}{*}{**Smokers [\%]**} \\ \cline{2-2} \cline{5-6}  & **Men** & & & & \\ \hline BC patients & 18 & 6 & 65 (\(\pm\)12.0) & 26.03 (\(\pm\)4.1) & 67 \\ Healthy Volunteers & 18 & 6 & 64 (\(\pm\)10.4) & 25.87 (\(\pm\)2.2) & 75 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Demographic characteristics of the studied groups. Figure 1: Observed differences in metabolic profiles of control and BC patients: (**A**) PCA score plot for positive ionization mode, with PC1 describing 12.8% of the variation and PC2 describing 5.5%, (**B**) PCA plot for negative ionization mode, with PC1 describing 13.6% of the variation and PC2 describing 5.5%, (**C**) Score plot of OPLS-DA model for positive ionization mode, with R2 = 85.2% and Q2 = 46%, (**D**) Score plot of OPLS-DA model for negative ionization mode, with R2 = 88.2% and Q2 = 43.3%, (**E**) Pathway analysis of differential metabolites in positive ionization mode, (**F**) Pathway analysis of differential metabolites in negative ionization mode.