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In the advanced stages, malignant melanoma (MM) has a very poor prognosis. Due to tremendous efforts in cancer research over the last 10 years, and the introduction of novel therapies such as targeted therapies and immunomodulators, the rather dark horizon of the median survival has dramatically changed from under 1 year to several years. With the advent of proteomics, deep-mining studies can reach low-abundant expression levels. The complexity of the proteome, however, still surpasses the dynamic range capabilities of current analytical techniques. Consequently, many predicted protein products with potential biological functions have not yet been verified in experimental proteomic data. This category of ‘missing proteins’ (MP) is comprised of all proteins that have been predicted but are currently unverified. As part of the initiative launched in 2016 in the USA, the European Cancer Moonshot Center has performed numerous deep proteomics analyses on samples from MM patients. In this study, nine MPs were clearly identified by mass spectrometry in MM metastases. Some MPs significantly correlated with proteins that possess identical PFAM structural domains; and other MPs were significantly associated with cancer-related proteins. This is the first study to our knowledge, where unknown and novel proteins have been annotated in metastatic melanoma tumour tissue.

The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass‐spectrometry‐based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein‐coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease., The MM500 meta‐study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. The melanoma proteome landscape, obtained by the analysis of 505 well‐annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. This data covers 65% and 74% of the predicted and identified human proteome, respectively.

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in‐depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients., The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in‐depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and sub‐cellular localization was annotated within both primary and metastatic melanoma.

Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.

Checkpoint blockade therapies have changed the clinical management of metastatic melanoma patients considerably, showing survival benefits. Despite the clinical success, not all patients respond to treatment or they develop resistance. Although there are several treatment predictive biomarkers, understanding therapy resistance and the mechanisms of tumor immune evasion is crucial to increase the frequency of patients benefiting from treatment. The PTEN gene is thought to promote immune evasion and is frequently mutated in cancer and melanoma. Another feature of melanoma tumors that may affect the capacity of escaping T-cell recognition is melanoma cell dedifferentiation characterized by decreased expression of the microphtalmia-associated transcription factor (MITF) gene. In this study, we have explored the role of PTEN in prognosis, therapy response, and immune escape in the context of MITF expression using immunostaining and genomic data from a large cohort of metastatic melanoma. We confirmed in our cohort that PTEN alterations promote immune evasion highlighted by decreased frequency of T-cell infiltration in such tumors, resulting in a worse patient survival. More importantly, our results suggest that dedifferentiated PTEN negative melanoma tumors have poor patient outcome, no T-cell infiltration, and transcriptional properties rendering them resistant to targeted- and immuno-therapy.

Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.

In general, melanoma can be considered as a UV-driven disease with an aggressive metastatic course and high mutational load, with only few tumors (acral, mucosal, and uveal melanomas) not induced by sunlight and possessing a lower mutational load. The most commonly activated pathway in melanoma is the mitogen-activated protein kinase (MAPK) pathway. However, the prognostic significance of mutational stratification is unclear and needs further investigation. Here, in silico we combined mutation data from 162 melanomas subjected to targeted deep sequencing with mutation data from three published studies. Tumors from 870 patients were grouped according to BRAF, RAS, NF1 mutation or triple-wild-type status and correlated with tumor and patient characteristics. We found that the NF1-mutated subtype had a higher mutational burden and strongest UV mutation signature. Searching for co-occurring mutated genes revealed the RASopathy genes PTPN11 and RASA2, as well as another RAS domain-containing gene RASSF2 enriched in the NF1 subtype after adjustment for mutational burden. We found that a larger proportion of the NF1-mutant tumors were from males and with older age at diagnosis. Importantly, we found an increased risk of death from melanoma (disease-specific survival, DSS; HR, 1.9; 95% CI, 1.21-3.10; P = 0.046) and poor overall survival (OS; HR, 2.0; 95% CI, 1.28-2.98; P = 0.01) in the NF1 subtype, which remained significant after adjustment for age, gender, and lesion type (DSS P = 0.03, OS P = 0.06, respectively). Melanoma genomic subtypes display different biological and clinical characteristics. The poor outcome observed in the NF1 subtype highlights the need for improved characterization of this group.

Background BRAF and NRAS mutations are frequently found in melanoma tumours, and recently developed BRAF-targeted therapies demonstrate significant clinical benefit. Objectives We sought to investigate the clinical significance of BRAF and NRAS mutations in a clinic-based metastatic melanoma cohort. Methods In total, 237 tumours, mostly metastatic lesions, from 203 patients were screened for mutations in exon 15 of BRAF and exon 2 of NRAS using Sanger sequencing. BRAF and NRAS mutation status was analysed in relation to clinical and histopathological characteristics, and outcome. Results Mutation in BRAF and NRAS was present in 43% (88% V600E, 10% V600K) and 30% (48% Q61K, 40% Q61R) of metastatic melanomas, respectively. We found consistent BRAF and NRAS mutation status in all but one of 27 patients with multiple metastases. BRAF mutation was associated with younger age at primary diagnosis (P = 0.02). Among patients with distant metastatic melanoma, patients with BRAF-mutant tumours without BRAF inhibitor treatment had inferior survival compared with patients with BRAF inhibitor treatment [hazard ratio (HR) 2.35, 95% confidence interval (CI) 1.10-5.01, P = 0.03]. We also observed a trend towards better prognosis for patients with wild-type and NRAS-mutant tumours compared with BRAF V600E-mutant tumours (HR 0.64, 95% CI 0.39-1.04, P = 0.07; and HR 0.76, 95% CI 0.48-1.21, P = 0.25, respectively). Conclusions We were able to confirm the effect of BRAF inhibitor treatment in a single clinical institution. The results suggest further that BRAF mutation is a weak prognostic factor but a strong predictive factor and that BRAF-mutant melanoma might constitute one or more distinct subtypes of the disease with certain aetiology and clinical outcome.

Purpose: For primary melanomas, tumor thickness, mitotic rate, and ulceration are well-laid cornerstones of prognostication. However, a molecular exposition of melanoma aggressiveness is critically missing. We recently uncovered a four-class structure in metastatic melanoma, which predicts outcome and informs biology. This raises the possibility that a molecular structure exists even in the early stages of melanoma and that molecular determinants could underlie histophenotype and eventual patient outcome. Experimental Design: We subjected 223 archival primary melanomas to a horizontally integrated analysis of RNA expression, oncogenic mutations at 238 lesions, histomorphometry, and survival data. Results: Our previously described four-class structure that was elucidated in metastatic lesions was evident within the expression space of primary melanomas. Because these subclasses converged into two larger prognostic and phenotypic groups, we used the metastatic lesions to develop a binary subtype-based signature capable of distinguishing between “high” and “low” grade forms of the disease. The two-grade signature was subsequently applied to the primary melanomas. Compared with low-grade tumors, high-grade primary melanomas were significantly associated with increased tumor thickness, mitotic rate, ulceration (all P < 0.01), and poorer relapse-free (HR = 4.94; 95% CI, 2.84–8.59), and overall (HR = 3.66; 95% CI, 2.40–5.58) survival. High-grade melanomas exhibited elevated levels of proliferation and BRCA1/DNA damage signaling genes, whereas low-grade lesions harbored higher expression of immune genes. Importantly, the molecular-grade signature was validated in two external gene expression data sets. Conclusions: We provide evidence for a molecular organization within melanomas, which is preserved across all stages of disease. Clin Cancer Res; 18(15); 4026–36. ©2012 AACR.