Chen Na, Rong Ming, Shao Xiaoguang, Zhang Heng, Liu Shupeng, Dong Baijun, Xue Wei, Wang Tingyun, Li Taihao, Pan Jiahua
Key Laboratory of Specialty Fiber Optics and Optical Access Networks, School of Communication and Information Engineering, Shanghai University.
Department of Urology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai.
Int J Nanomedicine. 2017 Jul 27;12:5399-5407. doi: 10.2147/IJN.S137756. eCollection 2017.
The surface-enhanced Raman spectroscopy (SERS) of blood serum was investigated to differentiate between prostate cancer (PCa) and benign prostatic hyperplasia (BPH) in males with a prostate-specific antigen level of 4-10 ng/mL, so as to reduce unnecessary biopsies. A total of 240 SERS spectra from blood serum were acquired from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis. Multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms, were used to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa. Similarly, this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%. The results suggest that analyzing blood serum using SERS combined with PCA-LDA diagnostic algorithms is a promising clinical tool for PCa diagnosis and assessment.
研究了血清的表面增强拉曼光谱（SERS），以区分前列腺特异性抗原水平为4-10 ng/mL的男性前列腺癌（PCa）和良性前列腺增生（BPH），从而减少不必要的活检。从40名PCa患者和40名BPH患者中采集了总共240份血清的SERS光谱，这些患者均接受了前列腺活检并得到了病理诊断。使用包括主成分分析（PCA）和线性判别分析（LDA）诊断算法在内的多变量统计技术，分析了对照组（CTR）、PCa组和BPH组患者血清的光谱数据；结果显示，CTR组的灵敏度为97.5%，特异性为100.0%，精确度为100.0%，准确率为99.2%；BPH组的灵敏度为90.0%，特异性为97.5%，精确度为94.7%，准确率为98.3%；PCa组的灵敏度为95.0%，特异性为93.8%，精确度为88.4%，准确率为94.2%。同样，该技术可以显著区分低风险和高风险PCa，准确率为92.3%，特异性为95%，灵敏度为89.5%。结果表明，使用SERS结合PCA-LDA诊断算法分析血清是一种有前景的用于PCa诊断和评估的临床工具。
