| Project/Area Number |
18H02631
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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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| Review Section |
Basic Section 49020:Human pathology-related
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| Research Institution | Oita University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
泥谷 直樹 大分大学, 医学部, 准教授 (80305036)
守山 正胤 大分大学, 医学部, 教授 (90239707)
平下 有香 大分大学, 医学部, 医員 (70771955)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥16,770,000 (Direct Cost: ¥12,900,000、Indirect Cost: ¥3,870,000)
Fiscal Year 2020: ¥6,760,000 (Direct Cost: ¥5,200,000、Indirect Cost: ¥1,560,000)
Fiscal Year 2019: ¥6,630,000 (Direct Cost: ¥5,100,000、Indirect Cost: ¥1,530,000)
Fiscal Year 2018: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
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| Keywords | 癌オルガノイド / 早期反応性マーカー / 抗癌剤 / オルガノイド / 胃癌 / 感受性試験 / 個別化医療 / 抗がん剤 |
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| Outline of Final Research Achievements |
Prediction of therapy outcome is important to optimize therapeutic strategy for individual patients because drug efficacy varies widely among cancer patients. Patient derived tumor organoids (PDOs) are three-dimensional (3D) tumor cell cultures from primary tumors. PDOs potentially offer great benefits as a preclinical cancer model because they closely recapitulate morphological and genetic features in matched original tumor tissue. Furthermore, success rates for establishment of PDOs are generally higher than those of traditional 2D cell lines among various types of tumors. Previously, we suggested that early response after the drug treatment could predict an efficacy of the drug. Based on the data, we proposed diagnostic model using such biomarkers (ERM; Early Response Marker) to predict drug efficacies. Here, we aimed to establish the diagnostic system by using PDOs in combination with ERM.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究は抗癌剤効果予測法の確立を目指すものであり、癌化学療法適応患者が対象となる。例えば、国内で食道、胃、大腸、膵癌の化学療法適応患者は年間99,000人である（2016年度厚労省）。抗癌剤効果は患者により異なる。副作用の低減と高い治療効果のためには適した抗癌剤の選択、すなわち個別化医療が必須である。現行のがん個別化医療は遺伝子異常を標的とした分子病的薬が使われているため、遺伝子異常を標的としない抗癌剤の効果予測は困難である（細胞障害性抗癌剤など）。本研究はその課題を解決し、遺伝子異常では効果予測が困難な抗癌剤の効果予測法確立を目指しており、より多くの癌患者の個別化医療に貢献すると確信する。
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