Identification of a Robust Methylation Classifier for Cutaneous Melanoma Diagnosis.

ABSTRACT

Early diagnosis improves melanoma survival, yet the histopathological diagnosis of cutaneous primary melanoma can be challenging, even for expert dermatopathologists. Analysis of epigenetic alterations, such as DNA methylation, that occur in melanoma can aid in its early diagnosis. Using a genome-wide methylation screening, we assessed CpG methylation in a diverse set of 89 primary invasive melanomas, 73 nevi, and 41 melanocytic proliferations of uncertain malignant potential, classified based on interobserver review by dermatopathologists. Melanomas and nevi were split into training and validation sets. Predictive modeling in the training set using ElasticNet identified a 40-CpG classifier distinguishing 60 melanomas from 48 nevi. High diagnostic accuracy (area under the receiver operator characteristic curve = 0.996, sensitivity = 96.6%, and specificity = 100.0%) was independently confirmed in the validation set (29 melanomas, 25 nevi) and other published sample sets. The 40-CpG melanoma classifier included homeobox transcription factors and genes with roles in stem cell pluripotency or the nervous system. Application of the 40-CpG melanoma classifier to the diagnostically uncertain samples assigned melanoma or nevus status, potentially offering a diagnostic tool to assist dermatopathologists. In summary, the robust, accurate 40-CpG melanoma classifier offers a promising assay for improving primary melanoma diagnosis.