| Project/Area Number |
18591533
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Digestive surgery
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| Research Institution | Japanese Foundation For Cancer Research |
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Principal Investigator |
AKIO Saiura Japanese Foundation For Cancer Research, Cancer Institute, Researcher (70345221)
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| Co-Investigator(Kenkyū-buntansha) |
HOSHIKAWA Yutaka Japanese Foundation for Cancer Research, Cancer Institute, Researcher (80280626)
OHSAWA Yukio University of Tokyo, School of Engineering, Research Center of Advanced and Cancer Institute, Researcher Science Technology, Professor(full-time gestalt) (20273609)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥300,000)
Fiscal Year 2007: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2006: ¥2,600,000 (Direct Cost: ¥2,600,000)
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| Keywords | DNA microarray / Liver cancer |
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| Research Abstract |
RESEARCH RESULTS
Intrahepatic cholangiocarcinoma (ICC) is the second most common malignant tumor of the liver, and ICC is reportedly increasing recently. Liver is a frequent site of metastasis from cancer in various cancers. Adenocarcinoma is a popular histological type of cancer. Most of the gastrointestinal cancer is adenocarcinoma histologically. The treatment and prognosis differ for patients with these malignancies. The distinction between primary intrahepatic cholangiocarcinoma and metastatic adenocarcinoma is impossible. In this study, we applied DNA microarray technology to determine the origin of liver malignant tumors. Using Affymetrix U133A plus2.0 Gene Chip containing approximately 57000 transcripts (Affymetrix, USA), RNA samples from 40 patients with primary and metastatic liver adenocarcinomas (intrahepatic cholangiocarcinoma n=11, metastases from colorectal cancer n=20, metastases from gastric cancer n=8). Unsupervised and supervised class prediction approaches were used to identify gene markers that can discriminate the three groups. Three groups were successfully clustered by unsupervised clustering. Gene expression profiling identified a 126-gene signature that can discriminate the three groups. Prospectively, this signature was validated in 9 independent patients. The accuracy was 98%. In conclusion, we showed that gene expression profiling could elucidate the origin of the liver adenocarcinomas.
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