Project description:Liver metastasis is one of the major causes of death in colorectal cancer (CRC) patients. To understand this process, we investigated whether the gene expression profiling of matched colorectal carcinomas and liver metastases could reveal key molecular events involved in tumor progression and metastasis. We performed experiments using a cDNA microarray containing 17,104 genes with the following tissue samples: paired tissues of 25 normal colorectal mucosa, 27 primary colorectal tumors, 13 normal liver and 27 liver metastasis, and 20 primary colorectal tumors without liver metastasis. To remove the effect of normal cell contamination, we selected 4,583 organ-specific genes with a false discovery rate (FDR) of 0.0067% by comparing normal colon and liver tissues using significant analysis of microarray, and these genes were excluded from further analysis. We then identified and validated 46 liver metastasis-specific genes with an accuracy of 83.3% by comparing the expression of paired primary colorectal tumors and liver metastases using prediction analysis of microarray. The 46 selected genes contained several known oncogenes and 2 ESTs. To confirm that the results correlated with the microarray expression patterns, we performed RT-PCR with WNT5A and carbonic anhydrase II. Additionally, we observed that 21 of the 46 genes were differentially expressed (FDR = 2.27%) in primary tumors with synchronous liver metastasis compared with primary tumors without liver metastasis. We scanned the human genome using a cDNA microarray and identified 46 genes that may play an important role in the progression of liver metastasis in CRC. Keywords: gene expression profiling using cDNA microarray We performed 17K cDNA microarray with the amplified RNAs from the following tissue samples: normal colorectal mucosa, primary colorectal tumors, normal liver and liver metastasis tumors, and primary colorectal tumors without liver metastasis. Organ-specific genes in normal colon and liver tissues were excluded from the pre-filtered genes, and then we discovered and validated liver metastasis-specific genes commonly up-regulated in the primary colorectal tumors and liver metastasis tumors. To confirm the microarray data, we performed a RT-PCR of two genes (WNT5A and carbonic anhydrase II) in the primary colorectal tumors with and without liver metastases.
Project description:Liver metastasis is one of the major causes of death in colorectal cancer (CRC) patients. To understand this process, we investigated whether the gene expression profiling of matched colorectal carcinomas and liver metastases could reveal key molecular events involved in tumor progression and metastasis. We performed experiments using a cDNA microarray containing 17,104 genes with the following tissue samples: paired tissues of 25 normal colorectal mucosa, 27 primary colorectal tumors, 13 normal liver and 27 liver metastasis, and 20 primary colorectal tumors without liver metastasis. To remove the effect of normal cell contamination, we selected 4,583 organ-specific genes with a false discovery rate (FDR) of 0.0067% by comparing normal colon and liver tissues using significant analysis of microarray, and these genes were excluded from further analysis. We then identified and validated 46 liver metastasis-specific genes with an accuracy of 83.3% by comparing the expression of paired primary colorectal tumors and liver metastases using prediction analysis of microarray. The 46 selected genes contained several known oncogenes and 2 ESTs. To confirm that the results correlated with the microarray expression patterns, we performed RT-PCR with WNT5A and carbonic anhydrase II. Additionally, we observed that 21 of the 46 genes were differentially expressed (FDR = 2.27%) in primary tumors with synchronous liver metastasis compared with primary tumors without liver metastasis. We scanned the human genome using a cDNA microarray and identified 46 genes that may play an important role in the progression of liver metastasis in CRC. Keywords: gene expression profiling using cDNA microarray