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Melanoma risk loci as determinants of melanoma recurrence and survival

BACKGROUND: Steadily high melanoma mortality rates urge for the availability of novel biomarkers with a more personalized ability to predict melanoma clinical outcomes. Germline risk variants are promising candidates for this purpose; however, their prognostic potential in melanoma has never been sy...

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Detalles Bibliográficos
Autores principales: Rendleman, Justin, Shang, Shulian, Dominianni, Christine, Shields, Jerry F, Scanlon, Patrick, Adaniel, Christina, Desrichard, Alexis, Ma, Michelle, Shapiro, Richard, Berman, Russell, Pavlick, Anna, Polsky, David, Shao, Yongzhao, Osman, Iman, Kirchhoff, Tomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4228352/
https://www.ncbi.nlm.nih.gov/pubmed/24188633
http://dx.doi.org/10.1186/1479-5876-11-279
Descripción
Sumario:BACKGROUND: Steadily high melanoma mortality rates urge for the availability of novel biomarkers with a more personalized ability to predict melanoma clinical outcomes. Germline risk variants are promising candidates for this purpose; however, their prognostic potential in melanoma has never been systematically tested. METHODS: We examined the effect of 108 melanoma susceptibility single nucleotide polymorphisms (SNPs), associated in recent GWAS with melanoma and melanoma-related phenotypes, on recurrence-free survival (RFS) and overall survival (OS), in 891 prospectively accrued melanoma patients. Cox proportional hazards models (Cox PH) were used to test the associations between 108 melanoma risk SNPs and RFS and OS adjusted by age at diagnosis, gender, tumor stage, histological subtype and other primary tumor characteristics. RESULTS: We identified significant associations for rs7538876 (RCC2) with RFS (HR = 1.48, 95% CI = 1.20-1.83, p = 0.0005) and rs9960018 (DLGAP1) with both RFS and OS (HR = 1.43, 95% CI = 1.07-1.91, p = 0.01, HR = 1.52, 95% CI = 1.09-2.12, p = 0.01, respectively) using multivariable Cox PH models. In addition, we developed a logistic regression model that incorporates rs7538876, rs9960018, primary tumor histological type and stage at diagnosis that has an improved discriminatory ability to classify 3-year recurrence (AUC = 82%) compared to histological type and stage alone (AUC = 78%). CONCLUSIONS: We identified associations between melanoma risk variants and melanoma outcomes. The significant associations observed for rs7538876 and rs9960018 suggest a biological implication of these loci in melanoma progression. The observed predictive patterns of associated variants with clinical end-points suggest for the first time the potential for utilization of genetic risk markers in melanoma prognostication.