Abstract
BACKGROUND: Uveal melanoma is an aggressive cancer which has a high percentage metastasizing to the liver, with a worse prognosis. Identification of patients at high risk of metastases may provide information for early detection of metastases and treatment. METHODS: Expression profiling of ocular tumor tissues from 46 liver metastatic uveal melanoma samples and 45 non-metastatic uveal melanoma samples were got from GEO database. Bioinformatic analyses such as the Gene Oncology and Kyoto Encyclopedia of Genes and Genomes were used to identify genes and pathways specifically associated with liver metastases of the uveal melanoma. RESULTS: A total of 1138 probes were differentially expressed in two group samples. All differential gene interactions in the Signal-Net were analyzed. Of them, 768 probes were up-regulated and 370 down-regulated. They mainly participated in 125 GO terms and 16 pathways. Of the genes differentially expressed between two group cancers, HTR2B, CHL1, the ZNF family, YWHAZ and FYN were the most significantly altered. CONCLUSIONS: Bioinformatics may help excavate and analyze large amounts of data in microarrays by means of rigorous experimental planning, scientific statistical analysis and collection of complete data about liver metastases of uveal melanoma patients. In the present study, a novel differential gene expression pattern was constructed and advanced study will provide new targets for diagnosis and mechanism of uveal melanoma liver metastases.