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. 2015 Jan 1;21(1):175-83.
doi: 10.1158/1078-0432.CCR-13-3316.

Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma

Pedram Gerami  1 , Robert W Cook  2 , Jeff Wilkinson  3 , Maria C Russell  4 , Navneet Dhillon  5 , Rodabe N Amaria  6 , Rene Gonzalez  6 , Stephen Lyle  7 , Clare E Johnson  2 , Kristen M Oelschlager  2 , Gilchrist L Jackson  8 , Anthony J Greisinger  9 , Derek Maetzold  2 , Keith A Delman  4 , David H Lawson  4 , John F Stone  3
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Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma

Pedram Gerami et al. Clin Cancer Res. .

Abstract

Purpose: The development of a genetic signature for the identification of high-risk cutaneous melanoma tumors would provide a valuable prognostic tool with value for stage I and II patients who represent a remarkably heterogeneous group with a 3% to 55% chance of disease progression and death 5 years from diagnosis.

Experimental design: A prognostic 28-gene signature was identified by analysis of microarray expression data. Primary cutaneous melanoma tumor tissue was evaluated by RT-PCR for expression of the signature, and radial basis machine (RBM) modeling was performed to predict risk of metastasis.

Results: RBM analysis of cutaneous melanoma tumor gene expression reports low risk (class 1) or high risk (class 2) of metastasis. Metastatic risk was predicted with high accuracy in development (ROC = 0.93) and validation (ROC = 0.91) cohorts of primary cutaneous melanoma tumor tissue. Kaplan-Meier analysis indicated that the 5-year disease-free survival (DFS) rates in the development set were 100% and 38% for predicted classes 1 and 2 cases, respectively (P < 0.0001). DFS rates for the validation set were 97% and 31% for predicted classes 1 and 2 cases, respectively (P < 0.0001). Gene expression profile (GEP), American Joint Committee on Cancer stage, Breslow thickness, ulceration, and age were independent predictors of metastatic risk according to Cox regression analysis.

Conclusions: The GEP signature accurately predicts metastasis risk in a multicenter cohort of primary cutaneous melanoma tumors. Preliminary Cox regression analysis indicates that the signature is an independent predictor of metastasis risk in the cohort presented.

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