title: Differentiation of tumour-stage mycosis fungoides, psoriasis vulgaris and normal controls in a pilot study using serum proteomic analysis.
abstract: BACKGROUND
  Serum proteomic analysis is an analytical technique utilizing high-throughput mass spectrometry (MS) in order to assay thousands of serum proteins simultaneously. The resultant 'proteomic signature' has been used to differentiate benign and malignant diseases, enable disease prognosis, and monitor response to therapy.
  
  
  OBJECTIVE
  This pilot study was designed to determine if serum protein patterns could be used to distinguish patients with tumour-stage mycosis fungoides (MF) from patients with a benign inflammatory skin condition (psoriasis) and/or subjects with healthy skin.
  
  
  METHODS
  Serum was analysed from 45 patients with tumour-stage MF, 56 patients with psoriasis, and 47 controls using two MS platforms of differing resolution. An artificial intelligence-based classification model was constructed to predict the presence of the disease state based on the serum proteomic signature.
  
  
  RESULTS
  Based on data from an independent testing set (14-16 subjects in each group), MF was distinguished from psoriasis with 78.6% (or 78.6%) sensitivity and 86.7% (or 93.8%) specificity, while sera from patients with psoriasis were distinguished from those of nonaffected controls with 86.7% (or 93.8%) sensitivity and 75.0% (or 76.9%) specificity (depending on the MS platform used). MF was distinguished from unaffected controls with 61.5% (or 71.4%) sensitivity and 91.7% (or 92.9%) specificity. In addition, a secondary survival analysis using 11 MS peaks identified significant survival differences between two MF groups (all P-values <0.05).
  
  
  CONCLUSIONS
  Serum proteomics should be further investigated for its potential to identify patients with neoplastic skin disease and its ability to determine disease prognosis.
authors.affiliation: Dermatology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. cowene@mail.nih.gov
authors.forename: E W
authors.initials: EW
authors.lastname: Cowen
authors.forename: C-W
authors.initials: CW
authors.lastname: Liu
authors.forename: S M
authors.initials: SM
authors.lastname: Steinberg
authors.forename: S
authors.initials: S
authors.lastname: Kang
authors.forename: E C
authors.initials: EC
authors.lastname: Vonderheid
authors.forename: H S
authors.initials: HS
authors.lastname: Kwak
authors.forename: S
authors.initials: S
authors.lastname: Booher
authors.forename: E F
authors.initials: EF
authors.lastname: Petricoin
authors.forename: L A
authors.initials: LA
authors.lastname: Liotta
authors.forename: G
authors.initials: G
authors.lastname: Whiteley
authors.forename: S T
authors.initials: ST
authors.lastname: Hwang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001798:Blood Proteins / Q000737:chemistry*; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009182:Mycosis Fungoides / Q000097:blood* / Q000175:diagnosis; D010865:Pilot Projects; D040901:Proteomics / Q000379:methods; D011565:Psoriasis / Q000097:blood* / Q000175:diagnosis; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000097:blood* / Q000175:diagnosis
chemical_list: D001798:Blood Proteins