Data from A Genetic Expression Profile Associated with Oral Cancer Identifies a Group of Patients at High Risk of Poor Survival

Abstract

<div>Abstract<p><b>Purpose:</b> To determine if gene expression signature of invasive oral squamous cell carcinoma (OSCC) can subclassify OSCC based on survival.</p><p><b>Experimental Design:</b> 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.</p><p><b>Results:</b> 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 <i>LAMC2</i> (laminin γ<sub>2</sub>) 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 <i>LAMC2</i> or PCA. The area under the curve for models combining stage with either <i>LAMC2</i> or PCA was 0.80 or 0.82, respectively, compared with 0.70 for stage alone (<i>P</i> = 0.013 and 0.008, respectively).</p><p><b>Conclusions:</b> Gene expression and stage combined predict survival of OSCC patients better than stage alone.</p></div>