The molecular landscape of cutaneous melanoma and its clinical implications
Cutaneous melanoma arises due to the uncontrolled proliferation of melanocytes. It is the deadliest form of skin cancer and its incidence, particularly in younger adults, is rapidly rising worldwide. Over the past decade, multiple large-scale sequencing studies have uncovered the molecular landscape of cutaneous melanoma. In particular, an improved understanding of the melanoma genome and regulation of the immune system have led to the development of effective targeted and immunotherapies that have revolutionised the treatment landscape. Nevertheless, only a subset of patients demonstrate durable responses to these therapies and identifying those patients most likely to benefit remains an important unmet need. Melanoma is an aggressive malignancy that often metastasises beyond its primary site. It has a particular propensity to metastasise to the brain and the mechanisms underlying this devastating complication remain incompletely understood. Melanoma risk stratification has traditionally relied on the examination of clinical and pathological features, however it has become clear that traditional staging may fall short in accurately assessing an individual patients’ risk. There is therefore a need for robust prognostic biomarkers capable of identifying truly high-risk patients, or patients with biologically indolent tumours, which could be used as an adjunct to conventional clinicopathologic assessments, and would afford a unique insight into the underlying tumour cell biology. In this thesis, I explore the mutational landscape of cutaneous melanoma focussing on four key clinical cohorts; adolescent cutaneous melanoma, patients with brain metastases, widespread lethal metastatic disease and patients with high-risk primary melanoma. I use a range of high-throughput sequencing technologies to identify the tumour-specific somatic alterations characterising these cohorts and apply detailed multi-site phylogenetic analyses to uncover some of the key evolutionary changes. In the final chapter, I apply deep RNA sequencing to primary melanomas embedded within a prospective phase III clinical trial, to define and validate a gene expression signature identifying primary melanoma patients at higher risk of adverse outcomes. Together, these studies demonstrate how detailed analyses of molecular sequencing can uncover novel biological insights. It is hoped that further prospective molecular analyses coupled with high-quality experimental validation will pave the way towards novel therapeutic strategies for these patient cohorts.
melanoma, genomics, biomarkers, metastases
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