Prostate cancer is one of the most common malignancies of the older males worldwide. Early diagnosis and treatment are important to improve the survival of patients. Recently, we developed a new method for prostate cancer screening: by measuring the serum surface-enhanced Raman spectroscopy of prostate cancer patients and normal subjects, combining with classification algorithms of support vector machines, the measured surface-enhanced Raman spectroscopy spectra are successfully classified with accuracy of 98.1%. Although the practical application faces several difficulties, we believe that this label-free serum surface-enhanced Raman spectroscopy analysis technique combined with support vector machine diagnostic algorithms will become a powerful tool for noninvasive prostate cancer screening in the future.
Keywords: classification; prostate cancer; serum; support vector machine; surface enhanced Raman spectroscopy.