| Project/Area Number |
21592029
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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 |
Urology
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| Research Institution | Akita University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
HABUCHI Tomonori 秋田大学, 大学院・医学系研究科, 教授 (00293861)
HORIKAWA Yohei 秋田大学, 医学部, 講師 (40361232)
NARITA Shintaro 秋田大学, 医学部, 講師 (40396552)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2009: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | 腫瘍学 / 前立腺癌 / 予後予測 / 遺伝子多型 / SNPアレイ / 治療標的分子 / SNPパネル / 予後診断 / IGF-I / IGF-I受容体 / 免疫染色 |
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| Research Abstract |
Individual genetic variations may have a significant influence on the survival of metastatic prostate cancer (PCa) patients. We aimed to identify target genes and their variations involved in the survival of PCa patients using a single nucleotide polymorphism (SNP) panel. A total of 185 PCa patients with bone metastasis at initial diagnosis were analyzed. Each patient was genotyped using a Cancer SNP panel that contained 1421 SNPs in 408 cancer-related genes. SNPs associated with the survival were screened by log rank test. Fourteen SNPs in six genes, XRCC4, PMS1, GATA3, IL13, CASP8, and IGF1, were identified to have statistically significant association with the cancer-specific survival. The cancer-specific survivals of patients grouped according to the number of risk genotypes of 6 SNPs selected from the 14 SNPs differed significantly (0-1 vs 2-3 vs 4-6 risk genotypes, P = 7.20 × 10-8). The high-risk group was independently associated with the survival in a multivariate analysis that included conventional clinicopathological variables (P=1.8x10-7). We identified 14 SNPs in 6 cancer-related genes which were associated with poor survival in patients with metastatic PCa. A panel of SNPs may help predict the survival of those patients.
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