Gene signature of the metastatic potential of cutaneous melanoma: too much for too little?

It was expected that with the advent of genomics, oncology may defeat the deadliest forms of cancer including malignant melanoma, but the past years have indicated that this is not the case. Despite the stunning success of genomics in defining markers or gene signatures for breast cancer prognosis and predicting therapies, there is virtually no progression in malignant melanoma. This is happening when experimental oncology or metastasis research is using several rodent and human melanoma models, when our knowledge on the metastatic cascade is actually derived from these models. Our critical analysis of these studies revealed several factors which might be responsible for this failure. First, it is evident, that these studies must be based on rigorous sample collection and basic pathological considerations, where divergent histological types of melanoma cannot be analysed universally. Secondly, without following basic consideration of metastasis biology, the majority of these studies were rarely based on primary tumors but frequently on various types of regional metastases. Third, successful expression profiling studies on other tumors such as breast cancer, provided evidences that the homogeneity of the patient cohort at least by clinicopathological stage is a critical element when defining prognostic signatures. Four studies attempted to define the prognostic signature of skin melanoma but only one based the study on the primary tumor resulting in heterogenous signatures with a minimal overlap (MCM3 and NFKBIZ). Four study attempted to define the invasiveness-signature in the primary tumor based on thickness or growth pattern discrimination identifying a 9-gene overlap which proved to be different from the prognostic signatures. On the other hand, seven studies analyzed various types of metastatic tissues (rarely visceral-, mostly cutaneous or lymphatic metastases) to define the metastasis-signatures, again with minimal overlap (AQP3, LGALS7 and SFN). Using seven GEO-based melanoma datasets we have performed a meta-analysis of the metastasis-gene signatures using normalization protocols. This analysis identified a 350-gene signature, the core of which was a 17-gene signature characterizing locoregional metastases where the individual components occurred in 3 studies: several members of this signature were extensively studied before in context of melanoma metastasis including WNT5A, EGFR, BCL2A1 and OPN. These data suggest that only efficient inter-disciplinary collaboration throughout genomic analysis of human skin melanoma could lead to major advances in defining relevant gene-sets appropriate for clinical prognostication or revealing basic molecular pathways of melanoma progression.