title: A genetic expression profile associated with oral cancer identifies a group of patients at high risk of poor survival.
abstract: OBJECTIVE
  To determine if gene expression signature of invasive oral squamous cell carcinoma (OSCC) can subclassify OSCC based on survival.
  
  
  METHODS
  We analyzed the expression of 131 genes in 119 OSCC, 35 normal, and 17 dysplastic mucosa to identify cluster-defined subgroups. Multivariate Cox regression was used to estimate the association between gene expression and survival. By stepwise Cox regression, the top predictive models of OSCC-specific survival were determined and compared by receiver operating characteristic analysis.
  
  
  RESULTS
  The 3-year overall mean+/-SE survival for a cluster of 45 OSCC patients was 38.7+/-0.09% compared with 69.1+/-0.08% for the remaining patients. Multivariate analysis adjusted for age, sex, and stage showed that the 45 OSCC patient cluster had worse overall and OSCC-specific survival (hazard ratio, 3.31; 95% confidence interval, 1.66-6.58 and hazard ratio, 5.43; 95% confidence interval, 2.32-12.73, respectively). Stepwise Cox regression on the 131 probe sets revealed that a model with a term for LAMC2 (laminin gamma2) gene expression best identified patients with worst OSCC-specific survival. We fit a Cox model with a term for a principal component analysis-derived risk score marker and two other models that combined stage with either LAMC2 or PCA. The area under the curve for models combining stage with either LAMC2 or PCA was 0.80 or 0.82, respectively, compared with 0.70 for stage alone (P=0.013 and 0.008, respectively).
  
  
  CONCLUSIONS
  Gene expression and stage combined predict survival of OSCC patients better than stage alone.
authors.affiliation: Department of Otolaryngology-Head and Neck Surgery, University of Washington, Seattle, WA 98109-1024, USA.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Méndez
authors.forename: John R
authors.initials: JR
authors.lastname: Houck
authors.forename: David R
authors.initials: DR
authors.lastname: Doody
authors.forename: Wenhong
authors.initials: W
authors.lastname: Fan
authors.forename: Pawadee
authors.initials: P
authors.lastname: Lohavanichbutr
authors.forename: Tessa C
authors.initials: TC
authors.lastname: Rue
authors.forename: Bevan
authors.initials: B
authors.lastname: Yueh
authors.forename: Neal D
authors.initials: ND
authors.lastname: Futran
authors.forename: Melissa P
authors.initials: MP
authors.lastname: Upton
authors.forename: D Gregory
authors.initials: DG
authors.lastname: Farwell
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: Heagerty
authors.forename: Lue Ping
authors.initials: LP
authors.lastname: Zhao
authors.forename: Stephen M
authors.initials: SM
authors.lastname: Schwartz
authors.forename: Chu
authors.initials: C
authors.lastname: Chen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002294:Carcinoma, Squamous Cell / Q000235:genetics* / Q000401:mortality* / Q000473:pathology; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D009062:Mouth Neoplasms / Q000235:genetics* / Q000401:mortality*; D009367:Neoplasm Staging; D025341:Principal Component Analysis; D016016:Proportional Hazards Models; D020133:Reverse Transcriptase Polymerase Chain Reaction