Abstract
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.
Acknowledgements
The authors would like to acknowledge the financial support of the Medical Research Foundation of Guangdong Province (A2014466), Doctor Start Fund of Guangdong Medical College (XB1407), the National Natural Science Foundation of China (61335011, 61275187 and 31300691), Specialized Research Fund for the Doctoral Program of Higher Education of China (20114407110001), the Natural Science Foundation of Guangdong Province (9251063101000009) and the Cooperation Project in Industry, Education and Research of Guangdong province and Ministry of Education of China (2011A090200011).
Financial & competing interests disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
No writing assistance was utilized in the production of this manuscript.