title: Raman spectroscopy, a potential tool in diagnosis and prognosis of castration-resistant prostate cancer.
abstract: OBJECTIVE
  We evaluated the feasibility of Raman spectroscopy (RS) in diagnosis and prognosis of castration-resistant prostate cancer (CRPC) in patients with prostate cancer (PC).
  
  
  METHODS
  Raman spectra are detected from PC cell lines (LNCaP and C4-2) and tissues using a Labram HR 800 RS. Then, principal component analysis (PCA) and support vector machine (SVM) are applied for prediction. A leave-one-out cross-validation is used to train and test the SVM.
  
  
  RESULTS
  There are 50 qualified patients, including 33 with androgen-dependent prostate cancer (ADPC) and 17 with CRPC. The spectral changes at 1126, 1170, 1315 to 1338, and 1447  cm-1 between CRPC and ADPC are detected in both cells and tissues models, which are assigned to specific amino acids and DNA. PCA/SVM algorithm provided a sensitivity of 88.2% and a specificity of 87.9% for diagnosing CRPC tissues. Furthermore, 14 patients with ADPC progressed to CRPC within 12 months. These patients are separated into two groups depending on whether their cancers progressed to CRPC within 12 months. PCA/SVM could differentiate these two groups with a sensitivity of 85.7% and a specificity of 88.9%.
  
  
  CONCLUSIONS
  RS has the potential in diagnosis and prognosis of CRPC in clinical practice.
authors.affiliation: Xi'an Jiaotong University, First Affiliated Hospital of Medical College, Department of Urology, Xi'an, Shaanxi, China.
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
authors.forename: Dalin
authors.initials: D
authors.lastname: He
authors.forename: Jin
authors.initials: J
authors.lastname: Zeng
authors.forename: Zhenfeng
authors.initials: Z
authors.lastname: Guan
authors.forename: Qiang
authors.initials: Q
authors.lastname: Dang
authors.forename: Xinyang
authors.initials: X
authors.lastname: Wang
authors.forename: Jun
authors.initials: J
authors.lastname: Wang
authors.forename: Liqing
authors.initials: L
authors.lastname: Huang
authors.forename: Peilong
authors.initials: P
authors.lastname: Cao
authors.forename: Guanjun
authors.initials: G
authors.lastname: Zhang
authors.forename: JerTong
authors.initials: J
authors.lastname: Hsieh
authors.forename: Jinhai
authors.initials: J
authors.lastname: Fan
mesh_terms: D000465:Algorithms; D045744:Cell Line, Tumor; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D008297:Male; D025341:Principal Component Analysis; D011379:Prognosis; D064129:Prostatic Neoplasms, Castration-Resistant / Q000175:diagnosis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013059:Spectrum Analysis, Raman / Q000379:methods*; D060388:Support Vector Machine