| Project/Area Number |
26462124
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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 |
Respiratory surgery
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| Research Institution | The University of Tokyo |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
中島 淳 東京大学, 医学部附属病院, 教授 (90188954)
村川 知弘 東京大学, 医学部附属病院, 登録研究員 (50359626)
安樂 真樹 東京大学, 医学部附属病院, 特任准教授 (70598557)
似鳥 純一 東京大学, 医学部附属病院, 助教 (40424486)
北野 健太郎 東京大学, 医学部附属病院, 助教 (70647073)
垣見 和宏 東京大学, 医学部附属病院, 特任教授 (80273358)
松下 博和 東京大学, 医学部附属病院, 特任講師 (80597782)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Fiscal Year 2014: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | 肺癌 / 遺伝子変異 / パッセンジャー変異 / neoantigen / 個別化医療 / 網羅的遺伝子解析 / エクソーム / トランスクリプトーム / ネオアンチゲン / 肺癌個別化医療 / 肺癌遺伝子変異の網羅的同定 / 変異検出パイプライン構築 |
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| Outline of Final Research Achievements |
We developed algorithm to predict tumor specific antigens derive from somatic mutations, so called neoantigens, mostly from passenger mutations. We first identified somatic missense mutations in 6 primary lung cancer patients using multiple mutation-call softwares. Next, we added MHC binding prediction software and predicted candidate neoantigens in 15 lung cancer patients. Most of the predicted neoantigens derived from passenger mutations and were not shared among other patients. Finally, we combined transcriptome (RNAseq) data to exome-analysis pipeline to reduce false positives of expressed mutant mRNA. Thus, we developed efficient pipeline to target passenger mutation that could become candidate neoantigens using exome and RNAseq data.
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