Surface-enhanced Raman scattering (SERS) spectra were obtained from urine samples from subjects diagnosed with prostate cancer as well as from healthy controls, using Au nanoparticles as substrates. Principal component analysis (PCA) of the spectral data, followed by linear discriminant analysis (LDA), leads to a classification model with a sensitivity of 100 %, a specificity of 89 %, and an overall diagnostic accuracy of 95 %. Even considering the very limited number of samples involved in this report, preliminary results from this approach are extremely promising, encouraging further investigation.