Imaging Mass Spectrometry for the Classification of Melanoma Based on / Mutational Status.

Mutations of the oncogenes v-raf murine sarcoma viral oncogene homolog B1 () and neuroblastoma RAS viral oncogene homolog () are the most frequent genetic alterations in melanoma and are mutually exclusive. V600 mutations are predictive for response to the two inhibitors vemurafenib and dabrafenib and the mitogen-activated protein kinase kinase (MEK) inhibitor trametinib. However, inter- and intra-tumoral heterogeneity and the development of acquired resistance to inhibitors have important clinical implications. Here, we investigated and compared the molecular profile of and mutated and wildtype melanoma patients' tissue samples using imaging mass spectrometry-based proteomic technology, to identify specific molecular signatures associated with the respective tumors. SCiLSLab and R-statistical software were used to classify peptide profiles using linear discriminant analysis and support vector machine models optimized with two internal cross-validation methods (leave-one-out, k-fold). Classification models showed molecular differences between and mutated melanoma, and identification of both was possible with an accuracy of 87-89% and 76-79%, depending on the respective classification method applied. In addition, differential expression of some predictive proteins, such as histones or glyceraldehyde-3-phosphate-dehydrogenase, correlated with or mutation status. Overall, these findings provide a new molecular method to classify melanoma patients carrying and mutations and help provide a broader view of the molecular characteristics of these patients that may help understand the signaling pathways and interactions involving the altered genes.