| Project/Area Number |
17K10633
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Digestive surgery
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| Research Institution | Kobe University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
山下 公大 神戸大学, 医学部附属病院, 特命准教授 (80535427)
鈴木 知志 神戸大学, 医学研究科, 特命教授 (30457080)
掛地 吉弘 神戸大学, 医学研究科, 教授 (80284488)
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| Project Period (FY) |
2017-04-01 – 2020-03-31
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| Project Status |
Completed (Fiscal Year 2019)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2017: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 制御性B細胞 / 大腸癌腹膜播種 / 抗CD20抗体 / 分子標的薬 / 化学療法 / 大腸癌腹膜播腫 |
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| Outline of Final Research Achievements |
Cases of peritoneal dissemination of colorectal cancer have a poor prognosis because treatment for peritoneal recurrence is ineffective. In the present study, we used a colorectal cancer cell line to create a peritoneal seeding model. We clarified the dynamics of immune cells, especially MDSC and B10 cells. In a peritoneal seeding model, we used IVIS to capture the disease's progression and evaluated the temporal changes of intra-abdominal immune cells to show the accumulation of MDSCs directly. Besides, when compared with the same subcutaneous ingestion model, we were able to capture specific changes in disease progression and peritoneal dissemination. We have shown that elimination of PMN-MDSC delays the progression of the disease.
We also collected ascites from a cancer patient with peritoneal dissemination and confirmed the presence of M D S C in the ascites.
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| Academic Significance and Societal Importance of the Research Achievements |
消化器癌患者における腹膜播種患者における腹腔内MDSCやB細胞の機能に関しては、その制御も含め、不明な点が多い。これをマウスモデルでMDSCや制御性B 細胞の動態と機能を検証し、治療法を検討し、効果的な治療を開発することは学術的に意義があり、治療開発につながれば、臨床的なインパクトもある。さらに腹腔内MDSCや制御性B 細胞と治療効果を解析することができれば、患者ごとの適切な治療選択が可能となるため、有用性も高い。
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