Imaging Mass Spectrometry-Based Proteomic Analysis to Differentiate Melanocytic Nevi and Malignant Melanoma

SIMPLE SUMMARY: Histopathological, immunohistochemical and molecular investigation of melanocytic lesion is the standard for the diagnosis of melanocytic lesions that are difficult to classify. To ensure correct diagnosis, mass spectrometry has been proposed, specifically in the differential diagnosis of spitz nevi and melanoma. Imaging mass spectrometry is an evolving technology, able to discriminate various tumor entities, which combines morphological features and mass spectrometry. The aim of this study is to apply imaging mass spectrometry to melanocytic lesion to discriminate melanoma from nevi. ABSTRACT: The discrimination of malignant melanoma from benign nevi may be difficult in some cases. For this reason, immunohistological and molecular techniques are included in the differential diagnostic toolbox for these lesions. These methods are time consuming when applied subsequently and, in some cases, no definitive diagnosis can be made. We studied both lesions by imaging mass spectrometry (IMS) in a large cohort (n = 203) to determine a different proteomic profile between cutaneous melanomas and melanocytic nevi. Sample preparation and instrument setting were tested to obtain optimal results in term of data quality and reproducibility. A proteomic signature was found by linear discriminant analysis to discern malignant melanoma from benign nevus (n = 113) with an overall accuracy of >98%. The prediction model was tested in an independent set (n = 90) reaching an overall accuracy of 93% in classifying melanoma from nevi. Statistical analysis of the IMS data revealed mass-to-charge ratio (m/z) peaks which varied significantly (Area under the receiver operating characteristic curve > 0.7) between the two tissue types. To our knowledge, this is the largest IMS study of cutaneous melanoma and nevi performed up to now. Our findings clearly show that discrimination of melanocytic nevi from melanoma is possible by IMS.