Melanoma genomics

BRAF targets in melanoma. Biological mechanisms, resistance, and drug discovery. Cancer drug discovery and development. Volume 82. Ed. Ryan J. Sullivan. Springer (2015)

Recently, improving technologies, robust bioinformatics platforms, and declining costs of sequencing have made comprehensive analysis of melanoma mutations accessible. These analyses are complicated by tumor heterogeneity and the high mutation rate associated with melanoma. Genome sequencing has revealed that the rates of base mutation are higher in melanoma than in other solid tumors [111]. The elevated mutational load is almost entirely attributable to cytidine to thymidine (C > T) transitions, which can be induced by UVR exposure. Traditionally, C > T mutations at dipyrimidine sequences in the context of melanoma are considered UVB signature mutations while G > T mutations are attributed to oxidative damage mediated by UVA. However, many recurrent mutations in melanoma, including oncogenic BRAF and NRAS lesions, do not involve C > T or G > T base changes, suggesting that alternate mutagenic mechanisms may be involved.

The high somatic mutation rate in melanoma is an important challenge when discriminating between true driver mutations, which confer a fitness advantage to the tumor cell during melanomagenesis, and passenger mutations. A recent statistical approach to sequence analysis refined the predicted background passenger mutation rate to be heterogeneous rather than genome-uniform by allowing for variations associated with transcriptional status and location relative to exons. This approach infers positive selection at each locus based on the exon/intron distribution of mutations and predicted functional consequences of mutations. By this analysis, 46 and 9% of melanoma driver mutations can be attributed to C > T or G > T mutations, respectively, accounting for two-thirds of all non-BRAF or NRAS driver mutations [62].

Since the first genome of a melanoma cell line was published in 2010 [111], exome and whole-genome sequencing of patient tumors has identified multiple novel melanoma genes. In studies sampling up to 25 tumors, recurrent somatic mutations were identified in the downstream MAPK pathway components MAP3K5, MAP3K9, MEK1, and MEK2 [65, 66], ionotropic glutamate receptor GRIN2A [112], and the phosphatidylinositol 3,4,5-trisphosphate RAC exchange factor PREX2 [113].

In one report, GRIN2A mutations were found in one quarter of melanomas [112]. Although GRIN2A has not been functionally validated as an oncogene, glutamate receptor pathway dysregulation was previously implicated in melanoma in studies of another glutamate receptor, GRM3 [114]. Activated GRM3 is an accessory to MAPK signaling and can itself be mutated in melanomas [115]. PREX2 has been shown to negatively regulate PTEN in breast cancer and was mutated in 23 out of 107 melanomas in another study [113].

Whole-exome sequencing of larger melanoma cohorts, including 147 and 121 tumors respectively, identified novel melanoma genes including RAC1 and PPP6C [62, 116]. Recurrent mutations in both RAC1 and PPP6C result from C>T transitions. Somatic gain-of-function mutations in RAC1 were found in 5–10% of melanomas. These mutations destabilize Rac1’s inactive GDP-bound state and result in increased Rac1 activation, promoting cell proliferation and migration [116]. PPP6C encodes a serine/threonine phosphatase that was mutated in approximately 10% of melanomas. PPP6C acts as a tumor suppressor by negatively regulating levels of cyclin D1 (CCND1) during the G1 phase of the cell cycle. Thus, PPP6C loss-offunction mutations likely dysregulate cell cycle and mitosis in some melanomas.

[contact-form-7 id=»5168″ title=»Контактная форма 1″]


WordPress: 86.5MB | MySQL:1040 | 2,850sec