title: SELDI-TOF MS whole serum proteomic profiling with IMAC surface does not reliably detect prostate cancer.
abstract: BACKGROUND
  The analysis of bodily fluids using SELDI-TOF MS has been reported to identify signatures of spectral peaks that can be used to differentiate patients with a specific disease from normal or control patients. This report is the 2nd of 2 companion articles describing a validation study of a SELDI-TOF MS approach with IMAC surface sample processing to identify prostatic adenocarcinoma.
  
  
  METHODS
  We sought to derive a decision algorithm for classification of prostate cancer from SELDI-TOF MS spectral data from a new retrospective sample cohort of 400 specimens. This new cohort was selected to minimize possible confounders identified in the previous study described in the companion paper.
  
  
  RESULTS
  The resulting new classifier failed to separate patients with prostate cancer from biopsy-negative controls; nor did it separate patients with prostate cancer with Gleason scores <7 from those with Gleason scores > or =7.
  
  
  CONCLUSIONS
  In this, the 2nd stage of our planned validation process, the SELDI-TOF MS-based protein expression profiling approach did not perform well enough to advance to the 3rd (prospective study) stage. We conclude that the results from our previous studies-in which differentiation between prostate cancer and noncancer was demonstrated-are not generalizable. Earlier study samples likely had biases in sample selection that upon removal, as in the present study, resulted in inability of the technique to discriminate cancer from noncancer cases.
authors.affiliation: Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
authors.forename: Dale
authors.initials: D
authors.lastname: McLerran
authors.forename: William E
authors.initials: WE
authors.lastname: Grizzle
authors.forename: Ziding
authors.initials: Z
authors.lastname: Feng
authors.forename: Ian M
authors.initials: IM
authors.lastname: Thompson
authors.forename: William L
authors.initials: WL
authors.lastname: Bigbee
authors.forename: Lisa H
authors.initials: LH
authors.lastname: Cazares
authors.forename: Daniel W
authors.initials: DW
authors.lastname: Chan
authors.forename: Jackie
authors.initials: J
authors.lastname: Dahlgren
authors.forename: Jose
authors.initials: J
authors.lastname: Diaz
authors.forename: Jacob
authors.initials: J
authors.lastname: Kagan
authors.forename: Daniel W
authors.initials: DW
authors.lastname: Lin
authors.forename: Gunjan
authors.initials: G
authors.lastname: Malik
authors.forename: Denise
authors.initials: D
authors.lastname: Oelschlager
authors.forename: Alan
authors.initials: A
authors.lastname: Partin
authors.forename: Timothy W
authors.initials: TW
authors.lastname: Randolph
authors.forename: Lori
authors.initials: L
authors.lastname: Sokoll
authors.forename: Shiv
authors.initials: S
authors.lastname: Srivastava
authors.forename: Sudhir
authors.initials: S
authors.lastname: Srivastava
authors.forename: Mark
authors.initials: M
authors.lastname: Thornquist
authors.forename: Dean
authors.initials: D
authors.lastname: Troyer
authors.forename: George L
authors.initials: GL
authors.lastname: Wright
authors.forename: Zhen
authors.initials: Z
authors.lastname: Zhang
authors.forename: Liu
authors.initials: L
authors.lastname: Zhu
authors.forename: O John
authors.initials: OJ
authors.lastname: Semmes
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology; D000368:Aged; D000369:Aged, 80 and over; D015982:Bias; D014408:Biomarkers, Tumor / Q000097:blood*; D001800:Blood Specimen Collection; D016022:Case-Control Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism / Q000473:pathology; D040901:Proteomics; D012189:Retrospective Studies; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
chemical_list: D014408:Biomarkers, Tumor; D017430:Prostate-Specific Antigen