Patients with advanced metastatic melanoma have poor prognosis. Advances in genomic technologies have provided an unprecedented opportunity to interrogate its genetic landscape. Importantly, understanding of the molecular basis of melanoma, led to approved targeted therapies which increase survival time. However, the majority of melanoma patients do not respond to current therapeutic regimens and if responsive, tumors rapidly acquire drug resistance. As such, there remains a significant need to improve current treatments and combination therapies need to be assessed systematically. To this end we integrate functional and genetic techniques to comprehensively identify the drivers, co-drivers and drug resistance genes in melanoma. To genetically identify potential new drivers and co-drivers, we collated our whole exome and whole genome sequencing data with additional independent melanoma cohort datasets to systematically search for new genes involved in melanomagenesis. We identified recurrent mutations that may drive melanoma growth, survival or metastasis, and which may hold promise for the design of novel therapies to treat melanoma.
Importantly, our analysis not only identified novel recurrent non-synonymous mutations, but also recurrent synonymous mutations. Synonymous mutations, which do not alter the protein sequence and represent nearly a third of the coding mutations, are rarely investigated in the cancer genomics field. Our analysis identified for the first time a recurrent functional synonymous somatic mutation in BCL2L12 (F17F) which functionally affects its activity. Our data indicate that “silent” alterations have a role to play in human cancer, emphasizing the importance of their investigation in future cancer genome studies.
Notably, as more cancer genes become identified through sequencing approaches, attention will shift away from identification of cancer genes towards determining the functions they control. However, our understanding of the functional effects of identified mutations is hampered by the difficulty in assessing their biological effects in a physiological manner. This gap between our knowledge of genetic alterations and our understanding of their functional effects is a re-occurring theme in the cancer genetics field. To this end, we are establishing pioneering high-throughput applications of somatic cell knockout and somatic cell knockin technologies to evaluate melanoma drivers, co-drivers and drug resistance genes. These tools will make it possible to (i) decisively determine the function(s) of proteins that are intimately linked to the pathogenesis of melanoma; (ii) identify targetable mutations and co-targetable mutations; (iii) determine whether particular drug combinations inhibit melanoma cell growth more efficiently and bypass drug resistance.