| Project/Area Number |
20390392
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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 | 一般 |
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| Research Field |
Cerebral neurosurgery
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| Research Institution | Kyoto Prefectural University of Medicine (2010-2011)
Kurume University (2008-2009) |
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Principal Investigator |
YAMANAKA Ryuya 京都府立医科大学, 医学部, 教授 (20323991)
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| Co-Investigator(Kenkyū-buntansha) |
NISHIO Kazuto 近畿大学, 医学部, 教授 (10208134)
IKENAKA Kazuhiro 自然科学研究機構, 生理学研究所, 教授 (00144527)
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| Co-Investigator(Renkei-kenkyūsha) |
KAWAGUCHI Atsushi 久留米大学, バイオ統計センター, 講師 (60389319)
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| Project Period (FY) |
2008 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥15,470,000 (Direct Cost: ¥11,900,000、Indirect Cost: ¥3,570,000)
Fiscal Year 2011: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2010: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2009: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2008: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
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| Keywords | 脳腫瘍 / 中枢神経原発悪性リンパ腫 / 遺伝子発現プロファイル / マイクロアレイ / 分子標的療法 / ゲノム創薬 / 中枢神経系原発悪性リンパ腫 / 遺伝子発現情報 / 予後 / 脳リンパ腫 / 脳神経疾患 / 遺伝子発現解析 / マイクロRNA / SNP解析 / バイオマーカー / 化学療法 / 癌 / 糖鎖 / 臨床 |
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| Research Abstract |
Better understanding of the underlying biology of primary central nervous system lymphomas (PCNSLs) is critical for the development of early detection strategies, molecular markers, and new therapeutics. This study aimed to define genes associated with survival of PCNSL patients. Expression profiling was performed on 34 PCNSLs. A gene classifier was developed using the random survival forests model. Based on this, Prognosis Prediction Score(PPS) using immunohistochemical analysis is also developed and validated in another data set with 38 PCNSLs. We identified 21 genes whose expressions were strongly and consistently related to patient survival. A PPS was developed for overall survival using a univariate Cox model. Survival analyses using the selected 21 gene classifiers revealed a prognostic value for high-dose methotrexate (HD-MTX) and HD-MTX containingpolychemotherapy regimen-treated patients. PPS using immunohistochemical analysis is also significant in test and validation data set. The gene-based predictor was an independent prognostic factor in a multivariate model that included clinical risk stratification. We have identified gene expression signatures that can accurately predict survival in patients with PCNSL. These predictive genes should be useful as molecularbiomarkers and could provide novel targets for therapeutic interventions.
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