| Theme | Recent advances in the diagnostic imaging and the treatment of liver metastates from colorectal cancer | |
|---|---|---|
| Title | DNA array technology : anticipated impact on studies of colorectal liver metastasis | |
| Publish Date | 2003/05 | |
| Author | Kiyotaka Okuno | Department of Surgery, Kinki University School of Medicine |
| Author | Kiyohiko Inoue | Department of Surgery, Kinki University School of Medicine |
| Author | Tadao Tokoro | Department of Surgery, Kinki University School of Medicine |
| Author | Jin-ichi Hida | Department of Surgery, Kinki University School of Medicine |
| Author | Masayuki Yasutomi | Department of Surgery, Kinki University School of Medicine |
| [ Summary ] | A large number of markers related to liver metastasis are featured in medical literature. However, even though there are many claims as to their prognostic significance in colorectal liver metastasis, one question remains: which markers are most important? Recent DNA array technology has facilitated the analysis of variations in gene expression in hundreds to thousands of genes at once. To identify the genes responsible for liver metastasis, we compared gene expression patterns in colorectal cancer specimens from patients with/without liver metastases using a cDNA array. Complementary DNA probes were prepared from mRNA extracted from the specimens. Labeled probes were allowed to bind to the gene fragments on a DNA array filter, which spotted 1,300 cancer-related genes. Data sets from all experiments were first quality filtered and applied, using artificial neural network computer software. This analysis identified 55 genes whose expression was up-regulated, and 41 genes were down-regulated in the liver metastasis group. Applying the artificial neural networks, cancer specimens were separated clearly, depending on liver metastasis status. Interestingly, blinded samples for data validation were classified correctly according to this program. This study demonstrates the potential applications of these methods for predicting liver metastasis and the identification of candidate targets for therapy. | |