Genetics of melanoma

Abstract

Genomic variation is a trend observed in various human diseases including cancer. Genetic studies have set out to understand how and why these variations result in cancer, why some populations are pre-disposed to the disease, and also how genetics affect drug responses. The melanoma incidence has been increasing at an alarming rate worldwide. The burden posed by melanoma has made it a necessity to understand the fundamental signaling pathways involved in this deadly disease. Signaling cascades such as mitogen-activated protein kinase and PI3K/AKT have been shown to be crucial in the regulation of processes that are commonly dysregulated during cancer development such as aberrant proliferation, loss of cell cycle control, impaired apoptosis, and altered drug metabolism. Understanding how these and other oncogenic pathways are regulated has been integral in our challenge to develop potent anti-melanoma drugs.With advances in technology and especially in next generation sequencing, we have been able to explore melanoma genomes and exomes leading to the identification of previously unknown genes with functions in melanomagenesis such as GRIN2A and PREX2.The therapeutic potential of these novel candidate genes is actively being pursued with some presenting as druggable targets while others serve as indicators of therapeutic responses. In addition, the analysis of the mutational signatures of melanoma tumors continues to cement the causative role of UV exposure in melanoma pathogenesis. It has become distinctly clear that melanomas from sun-exposed skin areas have distinct mutational signatures including C to T transitions indicative of UV-induced damage. It is thus necessary to continue spreading awareness on how to decrease the risk factors of developing the disease while at the same time working for a cure. Given the large amount of information gained from these sequencing studies, it is likely that in the future, treatment of melanoma will follow a highly personalized route that takes into account the differential mutational signatures of each individual's cancer. © 2013 Wangari-Talbot and Chen.