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Julien Trolet, Philippe Hupé, Isabelle Huon, Ingrid Lebigot, Charles Decraene, Olivier Delattre, Xavier Sastre-Garau, Simon Saule, Jean-Paul Thiéry, Corine Plancher, Bernard Asselain, Laurence Desjardins, Pascale Mariani, Sophie Piperno-Neumann, Emmanuel Barillot, Jérôme Couturier; Genomic Profiling and Identification of High-Risk Uveal Melanoma by Array CGH Analysis of Primary Tumors and Liver Metastases. Invest. Ophthalmol. Vis. Sci. 2009;50(6):2572-2580. doi: 10.1167/iovs.08-2296.
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purpose. Incurable metastases develop in approximately 50% of patients with uveal melanoma (UM). The purpose of this study was to analyze genomic profiles in a large series of ocular tumors and liver metastases and design a genome-based classifier for metastatic risk assessment.
methods. A series of 86 UM tumors and 66 liver metastases were analyzed by using a BAC CGH (comparative genomic hybridization) microarray. A clustering was performed, and correlation with the metastatic status was sought among a subset of 71 patients with a minimum follow-up of 24 months. The status of chromosome 3 was further examined in the tumors, and metastases with disomy 3 were checked with an SNP microarray. A prognostic classifier was constructed using a log-linear model on minimal regions and leave-one-out cross-validation.
results. The clustering divides the groups of tumors with disomy 3 and monosomy 3 into two and three subgroups, respectively. Same subgroups are found in primary tumors and in metastases, but with different frequencies. Isolated monosomy 3 was present in 0% of metastatic ocular tumors and in 3% of metastases. The highest metastatic rate in ocular tumors was observed in a subgroup defined by the gain of 8q with a proximal breakpoint, and losses of 3, 8p, and 16q, also most represented in metastases. A prognostic classifier that included the status of these markers led to an 85.9% classification accuracy.
conclusions. The analysis of the status of these specific chromosome regions by genome profiling on SNP microarrays should be a reliable tool for identifying high-risk patients in future adjuvant therapy protocols.
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