Amplification of the 11q13 chromosomal region is a common event in primary melanomas. Several candidate genes are localized at this sequence; however, their role in melanoma has not been clearly defined. The aim of this study was to develop an accurate method for determining the amplification pattern of six candidate genes that map to this amplicon core and to elucidate the possible relationship between BRAF, NRAS mutations and CCND1 copy number alterations, all of which are key components of the MAP kinase pathway. Characterization of gene copy numbers was performed by quantitative PCR and, as an alternative method, fluorescence in situ hybridization was used to define the CCND1 amplification pattern at the single cell level. Samples with amplified CCND1 (32%) were further analyzed for copy number alterations for the TAOS1, FGF3, FGF19, FGF4 and EMS1 genes. Coamplification of the CCND1 and TAOS1 was present in 15% of tumors and was more frequent in ulcerated lesions (P ¼ 0.017). Furthermore, 56% of primary melanomas had either BRAF or NRAS mutations, but these two mutations were not present in any of the lesions analyzed. Of these cases, 34% also had CCND1 amplification. There was a significant relationship between NRAS activating mutations and UV exposure (P ¼ 0.005). We did not find correlations between CCND1 gene amplification status and any of the patients' clinicopathological parameters. However, CCND1 amplification simultaneously with either BRAF or NRAS activation mutations was observed mainly in primary tumors with ulcerated surfaces (P ¼ 0.028). We assume that coamplification of these candidate genes in the 11q13 region or CCND1 gene alterations along with either BRAF or NRAS mutations might be more important for prognosis than the presence of these alterations alone.

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We examine five quantitative models of the cell-cycle and cell-size control in Escherichia coli and Bacillus subtilis that have been proposed over the last decade to explain single-cell experimental data generated with high-throughput methods. After presenting the statistical properties of these models, we test their predictions against experimental data. Based on simple calculations of the defining correlations in each model, we first dismiss the stochastic Helmstetter-Cooper model and the Initiation Adder model, and show that both the Replication Double Adder and the Independent Double Adder model are more consistent with the data than the other models. We then apply a recently proposed statistical analysis method and obtain that the Independent Double Adder model is the most likely model of the cell cycle. By showing that the Replication Double Adder model is fundamentally inconsistent with size convergence by the adder principle, we conclude that the Independent Double Adder model is most consistent with the data and the biology of bacterial cell-cycle and cell-size control. Mechanistically, the Independent Adder Model is equivalent to two biological principles: (i) balanced biosynthesis of the cell-cycle proteins, and (ii) their accumulation to a respective threshold number to trigger initiation and division.