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

Pedram Gerami*, Robert W. Cook, Jeff Wilkinson, Maria C. Russell, Navneet Dhillon, Rodabe N. Amaria, Rene Gonzalez, Stephen Lyle, Clare E. Johnson, Kristen M. Oelschlager, Gilchrist L. Jackson, Anthony J. Greisinger, Derek Maetzold, Keith A. Delman, David H. Lawson, John F. Stone

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

122 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)175-183
Number of pages9
JournalClinical Cancer Research
Volume21
Issue number1
DOIs
StatePublished - Jan 1 2015

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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