Usefulness of metabolome analysis for predicting the effect of chemotherapy for unresectable colorectal cancer

Research Project

Project/Area Number	16K10554
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Research Field	Digestive surgery
Research Institution	Tokyo Medical University
Principal Investigator	Enomoto Masanobu 東京医科大学, 医学部, 講師 (40385018)
Co-Investigator(Kenkyū-buntansha)	砂村眞琴東京医科大学, 医学部, 兼任教授 (10201584) 杉本昌弘東京医科大学, 医学部, 教授 (30458963)
Project Period (FY)	2016-04-01 – 2020-03-31
Project Status	Completed (Fiscal Year 2019)
Budget Amount *help	¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000) Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000) Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000) Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Keywords	メタボローム / 大腸癌 / 化学療法 / 医学 / 腫瘍学
Outline of Final Research Achievements	The usefulness of metabolome analysis for the diagnosis of the presence of colorectal cancer has been shown and a separate report has been made. To examine the usefulness of metabolome analysis for predicting the effect of systemic chemotherapy on unresectable recurrent colorectal cancer, 53 cases have been accumulated so far. Initially, it was planned to collect and study 100 cases, but due to various reasons it was difficult to collect the planned cases. We have analyzed them, but at present, we have not proved that the metabolome analysis is useful for predicting the effect of systemic chemotherapy on unresectable recurrent colorectal cancer. One reason is that the number of cases is smaller than expected. The significance of the research itself is great, and we intend to continue the research by accumulating cases.
Academic Significance and Societal Importance of the Research Achievements	これまでに我々はメタボローム解析により「健常者」、「良性の大腸ポリープ患者」、「大腸癌患者」の診断が可能であることを報告してきた。また、大腸癌について転移再発を生じているか否かの診断も可能であることも明らかになりつつある。さらに本メタボローム解析研究が進むことで転移再発大腸癌に対する抗悪性腫瘍薬の効果を予測できるバイオマーカーが開発できれば、患者にとっては不要な副作用を避けることができ、国家にとっては医療費が抑制できることが予想される。現時点で証明できていないが本研究を継続することでより良い医療が提供可能となる。