| Project/Area Number |
12557114
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
Cerebral neurosurgery
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| Research Institution | HOKKAIDO UNIVERSITY |
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Principal Investigator |
MORIUCHI Tetsuya (2002) Hokkaido Univ. Institute for Genetic Medicine, Prof., 遺伝子病制御研究所, 教授 (20174394)
細川 眞澄男 (2000-2001) 北海道大学, 遺伝子病制御研究所, 教授 (20001901)
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| Co-Investigator(Kenkyū-buntansha) |
HOSOKAWA Masuo Health Sci. Univ. of Hokkaido, Sch. Of Nursing & Soc. Sci., Prof., 看護福祉学部, 教授 (20001901)
TADA Mitsuhiro Hokkaido Univ. Institute for Genetic Medicine, Asso. Prof., 遺伝子病制御研究所, 助教授 (10241316)
守内 哲也 北海道大学, 遺伝子病制御研究所, 教授 (20174394)
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| Project Period (FY) |
2000 – 2002
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| Project Status |
Completed (Fiscal Year 2002)
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| Budget Amount *help |
¥12,600,000 (Direct Cost: ¥12,600,000)
Fiscal Year 2002: ¥2,900,000 (Direct Cost: ¥2,900,000)
Fiscal Year 2001: ¥2,800,000 (Direct Cost: ¥2,800,000)
Fiscal Year 2000: ¥6,900,000 (Direct Cost: ¥6,900,000)
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| Keywords | glioblastoma / de novo glioblastoma / secondary glioblastoma / PI3K-Akt pathway / p53 functional loss / cDNA array / transcriptome / pattern classification / P13K-Aki pathway / p53 fumcional loss / cDNA aray / Pl3K-Ak1 pathway / PI3K-Akt pathway |
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| Research Abstract |
Glioblastoma multiforme is classified into two subsets : one is 'primary (de novo) glioblastoma' which arises in relatively elderly persons without a preceding lesion, and another is 'secondary glioblastoma' which arises in young persons with a preceding benign astrocytoma. The present study aimed to analyze mRNA expression profiles of the both subsets, disclose their underlying molecular pathological natures, and know the mechanism which causes the biological and clinical differences between the both subsets.
We obtained the following results through this study : 1) We developed a yeast-based stop codon assay to identify PTEN gene mutations that inversely correlate with p53 mutations to classify glioblastomas (Oncogene).
2) We developed an original DNA array consisting of 1300 genes. We analyzed 119 cancer cell lines including glioblastoma cells with the array, and obtained successful results.
3) We analyzed glioblastoma cell lines including U251MG, SF268, SF295, SF539, SNB-75, and SNB-78, for their p53-, APC- and PTEN-mutational states and their expression profiles. We identified a total of 85 genes that associated with the p53 mutational status.
4) We found that application of feature subset selection algorithms and neural networks to extract characteristic patterns of gene expression. We are now undertaking studies on a number of clinical cases of glioblastoma.
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