Purpose: To compare a gene expression-based classifier versus the standard genetic prognostic marker, monosomy 3, for predicting metastasis in uveal melanoma.
Experimental design: Gene expression profiling, fluorescence in situ hybridization (FISH), and array comparative genomic hybridization (aCGH) were done on 67 primary uveal melanomas. Clinical and pathologic prognostic factors were also assessed. Variables were analyzed by Cox proportional hazards, Kaplan-Meier analysis, sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratios.
Results: The gene expression-based molecular classifier assigned 27 tumors to class 1 (low risk) and 25 tumors to class 2 (high risk). By Cox univariate proportional hazards, class 2 signature (P = 0.0001), advanced patient age (P = 0.01), and scleral invasion (P = 0.007) were the only variables significantly associated with metastasis. Only the class 2 signature was needed to optimize predictive accuracy in a Cox multivariate model. A less significant association with metastasis was observed for monosomy 3 detected by aCGH (P = 0.076) and FISH (P = 0.127). The sensitivity and specificity for the molecular classifier (84.6% and 92.9%, respectively) were superior to monosomy 3 detected by aCGH (58.3% and 85.7%, respectively) and FISH (50.0% and 72.7%, respectively). Positive and negative predictive values (91.7% and 86.7%, respectively) and positive and negative likelihood ratios (11.9 and 0.2, respectively) for the molecular classifier were also superior to those for monosomy 3.
Conclusions: Molecular classification based on gene expression profiling of the primary tumor was superior to monosomy 3 and clinicopathologic prognostic factors for predicting metastasis in uveal melanoma.