Project/Area Number |
16K10510
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Digestive surgery
|
Research Institution | Kagoshima University |
Principal Investigator |
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Co-Investigator(Kenkyū-buntansha) |
佐々木 健 鹿児島大学, 医歯学域附属病院, 助教 (00418849)
喜多 芳昭 鹿児島大学, 医歯学域附属病院, 助教 (30570692)
大脇 哲洋 鹿児島大学, 医歯学域医学系, 教授 (50322318)
夏越 祥次 鹿児島大学, 医歯学域医学系, 教授 (70237577)
尾本 至 鹿児島大学, 附属病院, 医員 (90721217)
|
Project Period (FY) |
2016-04-01 – 2019-03-31
|
Project Status |
Completed (Fiscal Year 2018)
|
Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2018: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2016: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
|
Keywords | 食道癌 / 個別化治療 / N型糖鎖 / *食道癌 / N型糖鎖 |
Outline of Final Research Achievements |
We focused on N-glycans in plasma that distinguish between esophageal cancer patients and healthy individuals.We investigated whether we could predict the effect on the treatment of esophageal cancer patients. The N-glycans in the plasma of 48 patients with esophageal cancer were measured. As a result, we found sugar chains that changed before and after surgery, before and after radical chemoradiotherapy, and with or without therapeutic effects. Moreover, as a result of examining the biopsy sample of the endoscopy before treatment, the esophageal cancer causing the epithelial-mesenchymal transition had a poor therapeutic effect. The presence or absence of micrometastases in the dissected lymph nodes was associated with therapeutic effects. In other words, it was suggested that changes in sugar chains could be predictive of effects.
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Academic Significance and Societal Importance of the Research Achievements |
食道癌患者に対する治療の前後で血漿中のN型糖鎖の変化を測定することができた。実際に治療効果で変化のある糖鎖も指摘できたことで、どの糖鎖の組み合わせがより治療効果を反映しているかを判定し、治療前の生検での免疫生化学検査も組み合わせることにより、今後、食道道癌患者の治療を行うにあたり、血液検査によって、治療前に効果をより正確に予測することが可能となる。
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