Identification of recurrent mutation in the BRAF oncogene in melanoma has led to the development of highly selective kinase inhibitors (Larkin et al., 2014). Although dramatic treatment responses are initially observed, responses are rarely durable. The mutational classification based on BRAF, NRAS, and NF1 mutations that has been established, however, is nonoverlapping with classification derived from gene expression profiling (The Cancer Genome Atlas Network [TCGA], 2015; Jönsson et al., 2010). In 2010, we reported four expression-based melanoma subtypes (the Lund subtypes): the high-immune, normal-like, microphthalmia-associated transcription factor (MITF)-high pigmentation, and MITF-low proliferative groups (Jönsson et al., 2010). The high-immune group was distinguished by elevated expression of immune genes, the normal-like group by genes expressed in surrounding normal cells; the MITF-high pigmentation and the MITF-low proliferative groups displayed increased expression of cell-cycle genes, and the MITF-low proliferative group had decreased expression of melanocyte differentiation genes. These subtypes were derived in stage IV tumors (Jönsson et al., 2010), but have since been firmly established in primary tumors(Harbst et al., 2012; Nsengimana et al., 2015) and stage III tumors (Cirenajwis et al., 2015). In 2015, a TCGA landmark study reported three melanoma gene expression subtypes (TCGA, 2015). The immune group was characterized by increased expression of immune genes; the keratin group was characterized by overexpression of keratin, pigmentation and epithelial genes; and the MITF-low group displayed decreased expression of melanocyte differentiation genes and activation of genes involved in nervous system development. However, it is not clear how the biological processes underlying the classification schemes relate to each other. Here, we compare bioinformatically derived biological pathways between the TCGA and Lund subtypes to search for evidence that both classification schemes identify similar biological entities, which may prove to be relevant in patient care. To compare the TCGA and Lund classification schemes, we first investigated the two reported gene sets. Of the 1,500 TCGA genes used for subtype discovery, only 34 overlapped with the 486 Lund genes (Figure 1 a). Despite this limited overlap, gene ontology-term analysis showed similar biological processes enriched (false discovery rate< 0.01) in the two gene sets, including immunological processes (eg, immune response, TCGA; response to wounding, Lund), melanocyte development (eg, epidermis development, TCGA; pigmentation, Lund), and cell adhesion (eg, cellular adhesion, TCGA and Lund). In addition, neuronal development processes were enriched in the TCGA gene set alone (see Supplementary Figure S1 online). Next, we investigated whether absolute expression levels of the TCGA and Lund gene sets differed (see Supplementary Materials online). Most TCGA genes were expressed at remarkably low levels, whereas the Lund genes were drawn from the entire expression range (P ¼ 1 Â 10e68, Figure 1 A). This suggests that the limited gene overlap between the TCGA and Lund classification schemes was caused by the technical relationship of intensity and variance (see Supplementary Figure S1), not by biological divergence. Collectively, although the gene sets were obtained from different expression ranges, they represent similar biological processes. Next, we compared actual sample classifications between the TCGA and Lund schemes. First, we classified the 329 TCGA samples (TCGA, 2016)(Table 1 …