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Journal ArticleDOI

Distinct Sets of Genetic Alterations in Melanoma

TLDR
The genetic alterations identified in melanoma at different sites and with different levels of sun exposure indicate that there are distinct genetic pathways in the development of melanoma and implicate CDK4 and CCND1 as independent oncogenes in melanomas without mutations in BRAF or N-RAS.
Abstract
Background Exposure to ultraviolet light is a major causative factor in melanoma, although the relationship between risk and exposure is complex. We hypothesized that the clinical heterogeneity is explained by genetically distinct types of melanoma with different susceptibility to ultraviolet light. Methods We compared genome-wide alterations in the number of copies of DNA and mutational status of BRAF and N-RAS in 126 melanomas from four groups in which the degree of exposure to ultraviolet light differs: 30 melanomas from skin with chronic sun-induced damage and 40 melanomas from skin without such damage; 36 melanomas from palms, soles, and subungual (acral) sites; and 20 mucosal melanomas. Results We found significant differences in the frequencies of regional changes in the number of copies of DNA and mutation frequencies in BRAF among the four groups of melanomas. Samples could be correctly classified into the four groups with 70 percent accuracy on the basis of the changes in the number of copies of...

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Superior Outcome of Women With Stage I/II Cutaneous Melanoma: Pooled Analysis of Four European Organisation for Research and Treatment of Cancer Phase III Trials

TL;DR: Women have a consistent and independent relative advantage in all aspects of the progression of localized melanoma of approximately 30%, most likely caused by an underlying biologic sex difference.
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Analysis of the genome to personalize therapy for melanoma

TL;DR: The molecular targets that have been validated clinically, additional genetic events that are candidates for future trials, and the challenges that remain to improve outcomes further in this aggressive disease are discussed.
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Unraveling the crosstalk between melanoma and immune cells in the tumor microenvironment

TL;DR: An effective therapeutic strategy will require coordinate activation of tumor-specific immunity as well as increased recognition and accessibility of melanoma cells in primary tumors and distal metastases, and methods that have been developed to restore immunity are emphasized.
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G-quadruplexes: a promising target for cancer therapy.

TL;DR: In this article, a correlation between G4 structure formation and an increased intratumor heterogeneity was identified, which suggests that G4 structures might allow breast cancer stratification and support the identification of new personalized treatment options.
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Genome sequencing of mucosal melanomas reveals that they are driven by distinct mechanisms from cutaneous melanoma.

TL;DR: The data suggest that different mechanisms underlie the genesis of these diseases and that structural variations play a more important role in mucosal than in cutaneous melanomagenesis, and that mucosal andcutaneous melanomas are distinct diseases with discrete genetic features.
References
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Journal ArticleDOI

R: A Language for Data Analysis and Graphics

TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.
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A new regulatory motif in cell-cycle control causing specific inhibition of cyclin D/CDK4

TL;DR: P16 seems to act in a regulatory feedback circuit with CDK4, D-type cyclins and retinoblastoma protein, and inhibits the catalytic activity of theCDK4/cyclin D enzymes.
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Comparison of discrimination methods for the classification of tumors using gene expression data

TL;DR: Different discrimination methods for the classification of tumors based on gene expression data include nearest-neighbor classifiers, linear discriminant analysis, and classification trees, which are applied to datasets from three recently published cancer gene expression studies.
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