An attempt at a molecular prediction of metastasis in patients with primary cutaneous melanoma

• Published in: PloS one 2012-11, Vol.7 (11), p.e49865-e49865
• Main Authors: Gschaider, Melanie, Neumann, Friederike, Peters, Bettina, Lenz, Florian, Cibena, Michael, Goiser, Malgorzata, Wolf, Ingrid, Wenzel, Jörg, Mauch, Cornelia, Schreiner, Wolfgang, Wagner, Stephan N
• Format: Article
• Language: English
• Subjects: Analysis; Bioinformatics; Biology; Breast cancer; Care and treatment; CD24 antigen; Clinical trials; Datasets; Dermatology; Development and progression; DNA microarrays; Gene expression; Gene Expression Profiling; Gene Expression Regulation, Neoplastic - physiology; Genes; Genomics; Hazards; Humans; Immunology; Infectious diseases; Informatics; Mathematics; Medical diagnosis; Medical Oncology - methods; Medical prognosis; Medical research; Medical statistics; Medicine; Melanoma; Melanoma - metabolism; Melanoma - secondary; Metastases; Metastasis; Neoplasm Metastasis - diagnosis; Patients; Predictions; Predictive Value of Tests; Prognosis; Proportional Hazards Models; Proteins; Regression Analysis; Reproducibility; Skin cancer; Skin Neoplasms - pathology; Statistical models; Studies; Survival analysis; Vasodilator-stimulated phosphoprotein
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0049865

Current prognostic clinical and morphological parameters are insufficient to accurately predict metastasis in individual melanoma patients. Several studies have described gene expression signatures to predict survival or metastasis of primary melanoma patients, however the reproducibility among these studies is disappointingly low. We followed extended REMARK/Gould Rothberg criteria to identify gene sets predictive for metastasis in patients with primary cutaneous melanoma. For class comparison, gene expression data from 116 patients with clinical stage I/II (no metastasis) and 72 with III/IV primary melanoma (with metastasis) at time of first diagnosis were used. Significance analysis of microarrays identified the top 50 differentially expressed genes. In an independent data set from a second cohort of 28 primary melanoma patients, these genes were analyzed by multivariate Cox regression analysis and leave-one-out cross validation for association with development of metastatic disease. In a multivariate Cox regression analysis, expression of the genes Ena/vasodilator-stimulated phosphoprotein-like (EVL) and CD24 antigen gave the best predictive value (p = 0.001; p = 0.017, respectively). A multivariate Cox proportional hazards model revealed these genes as a potential independent predictor, which may possibly add (both p = 0.01) to the predictive value of the most important morphological indicator, Breslow depth. Combination of molecular with morphological information may potentially enable an improved prediction of metastasis in primary melanoma patients. A strength of the gene expression set is the small number of genes, which should allow easy reevaluation in independent data sets and adequately designed clinical trials.