Malignant melanoma of the skin is the most aggressive human cancer given that a primary tumor a few millimeters in diameter frequently has full metastatic competence. In view of that, revealing the genetic background of this potential may also help to better understand tumor dissemination in general. Genomic analyses have established the molecular classification of melanoma based on the most frequent driver oncogenic mutations (BRAF, NRAS, KIT) and have also revealed a long list of rare events, including mutations and amplifications as well as genetic microheterogeneity. At the moment, it is unclear whether any of these rare events have role in the metastasis initiation process since the major drivers do not have such a role. During lymphatic and hematogenous dissemination, the clonal selection process is evidently reflected by differences in oncogenic drivers in the metastases versus the primary tumor. Clonal selection is also evident during lymphatic progression, though the genetic background of this immunoselection is less clear. Genomic analyses of metastases identified further genetic alterations, some of which may correspond to metastasis maintenance genes. The natural genetic progression of melanoma can be modified by targeted (BRAF or MEK inhibitor) or immunotherapies. Some of the rare events in primary tumors may result in primary resistance, while further new genetic lesions develop during the acquired resistance to both targeted and immunotherapies. Only a few genetic lesions of the primary tumor are constant during natural or therapy-modulated progression. EGFR4 and NMDAR2 mutations, MITF and MET amplifications and PTEN loss can be considered as metastasis drivers. Furthermore, BRAF and MITF amplifications as well as PTEN loss are also responsible for resistance to targeted therapies, whereas NRAS mutation is the only founder genetic lesion showing any association with sensitivity to immunotherapies. Unfortunately, there are hardly any data on the possible organ-specific metastatic drivers in melanoma. These observations suggest that clinical management of melanoma patients must rely on the genetic analysis of the metastatic lesions to be able to monitor progression-associated changes and to personalize therapies.

Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Data on the KIT mutation rate in melanoma in the central European region is missing. Accordingly, in a cohort of 79 BRAF/ NRAS double wild type cutaneous melanoma and 17 mucosal melanoma KIT mutation was assessed by Sanger sequencing of exons 9,11,13,17 and 18. In this cutaneous melanoma cohort KIT mutation frequency was found to be 34/79 (43.04%) with a significantly higher rate in acrolentiginous melanoma (ALM) as compared to UV-induced common variants (20/34, 58.8% versus 14/45, 31.1%, p = 0.014). In the double wild type mucosal melanoma cohort the KIT mutation frequency was found to be comparable (41.2%). The actual frequency of KIT mutation in the original 227 patient cutaneous melanoma cohort was 34/ 227, 14.9%. Exon 11 was the most frequent mutation site (44.7%) followed by exon 9 (21.1%) equally characterizing UVinduced common histotypes and ALM tumors. In mucosal melanoma exon 9 was the most frequently involved exon followed by exon 13 and 17. KIT mutation hotspots were identified in exon 9 (c482/491/492), in exon 11 (c559,c572, c570), in exon 13 (c642), in exon 17 (c822) and in exon 18 (c853). The relatively high KIT mutation rate in cutaneous melanoma in this central-European cohort justifies regular testing of this molecular target in this entity, not only in mucosal variants.