2022 Fiscal Year Final Research Report
Data-driven approach to identify prognostic determinants and therapeutic targets for lung cancer
Project/Area Number |
21K17856
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 62010:Life, health and medical informatics-related
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Research Institution | Tokyo Medical and Dental University |
Principal Investigator |
Shimizu Hideyuki 東京医科歯科大学, M&Dデータ科学センター, 教授 (70826263)
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Project Period (FY) |
2021-03-01 – 2023-03-31
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Keywords | 人工知能 / 肺がん / 層別化 |
Outline of Final Research Achievements |
Lung cancer, a prominent cause of cancer-related deaths in Japan, necessitates enhanced control measures. This study identified a comprehensive set of factors influencing the treatment response and prognosis of non-small cell lung cancer, accounting for over 80% of all lung cancer cases, via sophisticated mathematical informatics analysis. A distinct form of artificial intelligence was established, capable of predicting responses to immunotherapy for lung cancer prior to the actual treatment. Utilizing a Bayesian approach and integrating prediction uncertainty, this investigation provides a solid foundation for future research endeavors.
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Free Research Field |
バイオインフォマティクス
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Academic Significance and Societal Importance of the Research Achievements |
がんの中でも肺がんが最も多く、その制圧は急務である。特に、がん免疫療法はおよそ2割の肺がん患者にしか効かないが、治療前に成否を予測することは非常に難しく、効果がなかった場合の高額な治療コストや副作用が社会問題になっている。理想的には、効果がある患者さんを事前に層別化してがん免疫療法を行うのが望ましい。本研究課題はまさにそれを具現化し、治療前の遺伝子発現情報や年齢性別等のプロファイルからがん免疫療法の応答性を予測したという点で学術的のみならず社会的意義が大きい。
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