Person:

Tsao, Hensin

Cutaneous malignancies, especially malignant melanoma, exhibit great genetic heterogeneity. As a result, some individuals and families have particularly increased risk due to genetic predisposition to the disease. The susceptibility alleles range from rarely occurring, heritable, high-risk variants to ubiquitously occurring low-risk variants. Although until now the focus has been mostly towards the familial high-risk genes, the development of genome-wide association studies has uncovered a number of moderate- to low-risk predisposition alleles. The ability to specifically identify genetic variation associated with visible pigmentation traits and disease risk has provided a much richer view of the genetics of cutaneous malignancies. In this review, we provide an update on the recently identified risk loci. Existing clinical data, combined with vast genome information, will provide a better understanding of the biology of disease, and increased accuracy in risk prediction.

An effective treatment for metastatic melanoma remains one of the most elusive goals in all of oncology. Several generations of therapeutic trials have yet to yield any agents that can significantly prolong survival for widespread disease. Despite this disheartening history, our understanding of the biology and molecular genetics of melanoma hold the promise of a new era of molecular targets. One pathway that appears to be universally activated in and critically needed for melanoma growth is the Ras/mitogen activated protein (MAP) kinase signaling cascade. Since the enzymatic functions of the signaling partners are well characterized, this pathway offers many potential “druggable” candidates including Braf, Mek and Ras itself. In this review, we describe this pathway in the context of melanoma tumorigenesis and discuss some of the current relevant pharmacologic treatments and clinical trials.

Clonal heterogeneity and selection underpin many biological processes including development and tumor progression. Combinatorial fluorescent protein expression in germline cells has proven its utility for tracking the formation and regeneration of different organ systems. Such cell populations encoded by combinatorial fluorescent proteins are also attractive tools for understanding clonal expansion and clonal competition in cancer. However, the assignment of clonal identity requires an analytical framework in which clonal markings can be parameterized and validated. Here we present a systematic and quantitative method for RGB analysis of fluorescent melanoma cancer clones. We then demonstrate refined clonal trackability of melanoma cells using this scheme.

Melanoma is the most deadly form of skin cancer with a yearly global incidence over 232,000 patients. Individuals with fair skin and red hair exhibit the highest risk for developing melanoma, with evidence suggesting the red/blond pigment known as pheomelanin may elevate melanoma risk through both UV radiation-dependent and -independent mechanisms. Although the ability to identify, characterize, and monitor pheomelanin within skin is vital for improving our understanding of the underlying biology of these lesions, no tools exist for real-time, in vivo detection of the pigment. Here we show that the distribution of pheomelanin in cells and tissues can be visually characterized non-destructively and noninvasively in vivo with coherent anti-Stokes Raman scattering (CARS) microscopy, a label-free vibrational imaging technique. We validated our CARS imaging strategy in vitro to in vivo with synthetic pheomelanin, isolated melanocytes, and the Mc1re/e, red-haired mouse model. Nests of pheomelanotic melanocytes were observed in the red-haired animals, but not in the genetically matched Mc1re/e; Tyrc/c (“albino-red-haired”) mice. Importantly, samples from human amelanotic melanomas subjected to CARS imaging exhibited strong pheomelanotic signals. This is the first time, to our knowledge, that pheomelanin has been visualized and spatially localized in melanocytes, skin, and human amelanotic melanomas.

Background: Gender disparity in melanoma outcome is consistently observed, suggesting that gender is as an important prognostic factor. However, the source of this gender disparity in melanoma remains unclear. Objective: This article reviews advances in our understanding of gender differences in melanoma and how such differences may contribute to outcomes. Methods: A broad literature search was conducted using the PubMed database, with search terms such as ‘gender differences in melanoma’ and ‘sex differences in melanoma.’ Additional articles were identified from cited references. Results: Herein, we address the gender-linked physiologic differences in skin and melanoma. We discuss the influence of estrogen on a woman’s risk for melanoma and melanoma outcomes with regard to pregnancy, oral contraceptives, hormone replacement therapy, and UV tanning. Conclusions: The published findings on gender disparities in melanoma have yielded many advances in our understanding of this disease. Biological, environmental, and behavioral factors may explain the observed gender difference in melanoma incidence and outcome. Further research will enable us to learn more about melanoma pathogenesis, with the goal of offering better treatments and preventative advice to our patients.

Melanoma is currently divided on a genetic level according to mutational status. However, this classification does not optimally predict prognosis. In prior studies, we have defined gene expression phenotypes (high-immune, pigmentation, proliferative and normal-like), which are predictive of survival outcome as well as informative of biology. Herein, we employed a population-based metastatic melanoma cohort and external cohorts to determine the prognostic and predictive significance of the gene expression phenotypes. We performed expression profiling on 214 cutaneous melanoma tumors and found an increased risk of developing distant metastases in the pigmentation (HR, 1.9; 95% CI, 1.05-3.28; P=0.03) and proliferative (HR, 2.8; 95% CI, 1.43-5.57; P=0.003) groups as compared to the high-immune response group. Further genetic characterization of melanomas using targeted deep-sequencing revealed similar mutational patterns across these phenotypes. We also used publicly available expression profiling data from melanoma patients treated with targeted or vaccine therapy in order to determine if our signatures predicted therapeutic response. In patients receiving targeted therapy, melanomas resistant to targeted therapy were enriched in the MITF-low proliferative subtype as compared to pre-treatment biopsies (P=0.02). In summary, the melanoma gene expression phenotypes are highly predictive of survival outcome and can further help to discriminate patients responding to targeted therapy.