| Project/Area Number |
16K08694
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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 |
Human pathology
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| Research Institution | Yokohama City University |
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Principal Investigator |
Tateishi Yoko 横浜市立大学, 医学部, 助教 (20644438)
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| Co-Investigator(Kenkyū-buntansha) |
奥寺 康司 横浜市立大学, 医学部, 准教授 (10326027)
梅田 茂明 横浜市立大学, 附属病院, 助教 (30644439)
稲山 嘉明 横浜市立大学, 附属市民総合医療センター, 教授 (10184730)
大橋 健一 横浜市立大学, 医学研究科, 教授 (40231203)
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
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| Keywords | 早期大腸癌 / リンパ節転移 / microRNA / 網羅的発現解析 / 網羅的解析 |
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| Outline of Final Research Achievements |
The purpose of this study is to identify the microRNAs (miRNA) expression profile in early (submucosal invasive) colorectal cancer (CRC) with lymph node metastasis. In two early CRC cases, the primary CRC elements and the lymph node metastasis elements were separately collected from formalin fixed paraffin embedded (FFPE) specimens by laser microdissection system. Total RNAs were extracted and then subjected to comprehensive miRNA expression analyses (Agilent Expression Array). Differentially expressed miRNAs in the lymph node metastasis elements, whose levels showed more than two folds changes in compared to those of the primary CRC elements, were picked up. miR-125b was obtained as the upregulated miRNA, while eight miRNAs including miR-1228 were obtained as the downregulated miRNAs.
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| Academic Significance and Societal Importance of the Research Achievements |
早期大腸癌は多くが内視鏡切除により根治できるが、約10％にリンパ節転移を伴い外科切除が必要となる。このような高悪性度病変の峻別は早期大腸癌の病理診断における重要な課題である。本研究では、リンパ節転移を伴う早期大腸癌の原発巣とリンパ転移巣のmicroRNA発現プロファイルを明らかにする。早期大腸癌の高悪性度病変を峻別する分子指標の同定することで、悪性度を予測するバイオマーカーとして臨床への応用が期待される。
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