2021 Fiscal Year Final Research Report
Large scale screening of pre-pathological models that enable early detection of diseases by deep learning
Project/Area Number |
17KT0049
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Research Category |
Grant-in-Aid for Scientific Research (B)
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Allocation Type | Multi-year Fund |
Section | 特設分野 |
Research Field |
Complex Systems Disease Theory
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Research Institution | The University of Tokyo |
Principal Investigator |
Michiue Tatsuo 東京大学, 大学院総合文化研究科, 教授 (10282724)
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Co-Investigator(Kenkyū-buntansha) |
越智 陽城 山形大学, 医学部, 准教授 (00505787)
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Project Period (FY) |
2017-07-18 – 2022-03-31
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Keywords | 癌ドライバー遺伝子 / CRISPR-Cas9システム / ネッタイツメガエル / 腫瘍形成 |
Outline of Final Research Achievements |
Recent studies have shown that the frequency of tumorigenesis is increased by multiple gene mutations, but the gene sets have not been fully identified. In this study, we aimed to comprehensively find a novel set of cancer driver genes by multiple gene knocking down by using CRISPR-Cas9 and Xenopus as a model animal. We also aimed to analyze the gene expression profile in tumor tissues. As a result, the assay system using Xenopus was established, and a novel gene set showing a tumor-specific decrease was found.
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Free Research Field |
発生生物学・分子生物学・幹細胞生物学
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Academic Significance and Societal Importance of the Research Achievements |
まだまだ理解が進んでいない癌ドライバー遺伝子セットを多数同定することができれば、癌の未発症状態が把握でき、疾病予測にもつながることが期待できる。また、実際に遺伝子セットの腫瘍形成能を調べる上で、飼育が容易で安価であるネッタイツメガエルを用いたアッセイ系が確立できれば、他の多くの腫瘍形成メカニズム解析にも貢献できると期待できる。
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