Prediction of liver metastasis after colorectal cancer using reverse transcription-polymerase chain reaction analysis of 10 genes

Purpose: Liver metastasis is one of the major types of recurrence after surgery for colorectal cancer. Traditional methods of predicting liver metastasis are limited in their accuracy, suggesting the need to develop new predictors. We developed a 10-gene signature that is closely associated with the development of liver metastasis after colorectal cancer. Patients and methods: We examined a total of 189 frozen specimens of primary colorectal cancers using both microarray and quantitative real-time reverse transcriptase-polymerase chain reaction (RT-PCR) analysis. Initially, we studied gene expression in colorectal cancer tissue from 160 randomly selected patients who had undergone surgical resection of colorectal cancer and evaluated the association between the level of gene expression and the occurrence of liver metastasis. We developed a gene-expression model for the prediction of liver metastasis based on the RT-PCR findings. We then used specimens from 29 other patients for validation. Results: The expression of 14 genes was correlated with liver metastasis according to both microarray and RT-PCR analysis. We constructed an accurate predictive model based on the results for 10 of these genes, which included epiregulin (EREG), amphiregulin (AREG), cyclooxygenase 2 (COX-2) and lymphocyte-specific protein tyrosine kinase (LCK). The 10-gene signature was an independent predictor of liver metastasis. The model was validated in the independent set of 29 patients. The predictive accuracy of the model in a test set of patients was 86.2%. Conclusion: The 10-gene signature identified in this study is closely associated with the occurrence of liver metastasis in colorectal cancer patients. (C) 2010 Elsevier Ltd. All rights reserved.