title: Melanoma prognostic model using tissue microarrays and genetic algorithms.
abstract: OBJECTIVE
  As a result of the questionable risk-to-benefit ratio of adjuvant therapies, stage II melanoma is currently managed by observation because available clinicopathologic parameters cannot identify the 20% to 60% of such patients likely to develop metastatic disease. Here, we propose a multimarker molecular prognostic assay that can help triage patients at increased risk of recurrence.
  
  
  METHODS
  Protein expression for 38 candidates relevant to melanoma oncogenesis was evaluated using the automated quantitative analysis (AQUA) method for immunofluorescence-based immunohistochemistry in formalin-fixed, paraffin-embedded specimens from a cohort of 192 primary melanomas collected during 1959 to 1994. The prognostic assay was built using a genetic algorithm and validated on an independent cohort of 246 serial primary melanomas collected from 1997 to 2004.
  
  
  RESULTS
  Multiple iterations of the genetic algorithm yielded a consistent five-marker solution. A favorable prognosis was predicted by ATF2 ln(non-nuclear/nuclear AQUA score ratio) of more than -0.052, p21(WAF1) nuclear compartment AQUA score of more than 12.98, p16(INK4A) ln(non-nuclear/nuclear AQUA score ratio) of < or = -0.083, beta-catenin total AQUA score of more than 38.68, and fibronectin total AQUA score of < or = 57.93. Primary tumors that met at least four of these five conditions were considered a low-risk group, and those that met three or fewer conditions formed a high-risk group (log-rank P < .0001). Multivariable proportional hazards analysis adjusting for clinicopathologic parameters shows that the high-risk group has significantly reduced survival on both the discovery (hazard ratio = 2.84; 95% CI, 1.46 to 5.49; P = .002) and validation (hazard ratio = 2.72; 95% CI, 1.12 to 6.58; P = .027) cohorts.
  
  
  CONCLUSIONS
  This multimarker prognostic assay, an independent determinant of melanoma survival, might be beneficial in improving the selection of stage II patients for adjuvant therapy.
authors.affiliation: Department of Pathology, Yale University School of Medicine, New Haven, CT 06520-8023, USA.
authors.forename: Bonnie E
authors.initials: BE
authors.lastname: Gould Rothberg
authors.forename: Aaron J
authors.initials: AJ
authors.lastname: Berger
authors.forename: Annette M
authors.initials: AM
authors.lastname: Molinaro
authors.forename: Antonio
authors.initials: A
authors.lastname: Subtil
authors.forename: Michael O
authors.initials: MO
authors.lastname: Krauthammer
authors.forename: Robert L
authors.initials: RL
authors.lastname: Camp
authors.forename: William R
authors.initials: WR
authors.lastname: Bradley
authors.forename: Stephan
authors.initials: S
authors.lastname: Ariyan
authors.forename: Harriet M
authors.initials: HM
authors.lastname: Kluger
authors.forename: David L
authors.initials: DL
authors.lastname: Rimm
mesh_terms: D051698:Activating Transcription Factor 2 / Q000032:analysis; D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis*; D019941:Cyclin-Dependent Kinase Inhibitor p16 / Q000032:analysis; D050759:Cyclin-Dependent Kinase Inhibitor p21 / Q000032:analysis; D018572:Disease-Free Survival; D005260:Female; D006801:Humans; D008297:Male; D008545:Melanoma / Q000737:chemistry* / Q000401:mortality / Q000556:secondary; D008875:Middle Aged; D011379:Prognosis; D040081:Protein Array Analysis; D012878:Skin Neoplasms / Q000737:chemistry* / Q000401:mortality / Q000473:pathology; D015996:Survival Rate; D046888:Tissue Array Analysis; D051176:beta Catenin / Q000032:analysis
chemical_list: D051698:Activating Transcription Factor 2; D014408:Biomarkers, Tumor; C493956:CDKN1A protein, human; D019941:Cyclin-Dependent Kinase Inhibitor p16; D050759:Cyclin-Dependent Kinase Inhibitor p21; D051176:beta Catenin