Genomic Profiling and Identification of High-Risk Uveal Melanoma by Array CGH Analysis of Primary Tumors and Liver Metastases

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. 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. 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. 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.