Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients.,We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature.,This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10−5) and overall survival (HR = 1.61, p = 1.67 × 10−4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets.,The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10−4), or published prognostic signatures (pAUROC < 0.05).,The signature score negatively correlated with measures of immune cell infiltration (ρ = −0.75, p < 2.2 × 10−16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma.,Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.,The identification of prognostic biomarkers can help stratify cancer patients.,Here, the authors apply deep RNA sequencing from primary melanomas coupled with long-term clinical outcome data from a prospective multicentre phase III trial, to develop and validate a 121 metastasis-associated gene signature identifying early-stage melanoma patients at higher risk of metastasis and worse survival.
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.