Assessment of micro residual disease with ultra deep sequencing

• Project/Area Number: 26670492
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Pediatrics
• Research Institution: National Center for Child Health and Development (2015); The University of Tokyo (2014)
• Principal Investigator: Kato Motohiro 国立研究開発法人国立成育医療研究センター, その他部局等, その他 (40708690)
• Co-Investigator(Renkei-kenkyūsha): Takita Junko 東京大学, 小児科, 准教授 (00359621)
• Project Period (FY): 2014-04-01 – 2016-03-31
• Project Status: Completed (Fiscal Year 2015)
• Budget Amount: ¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000); Fiscal Year 2015: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000); Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
• Keywords: 白血病 / バイオマーカー / 癌 / 小児白血病

Outline of Final Research Achievements

To improve “stratification strategy based on prognostic factors”, we planned to establish detection system of micro residual disease (miRD) with higher sensitivity compared to standard methods. First, we assessed sensitivity using virtual tumor specimen with serial dilution by next generation sequencer, and 10-3 to 10-4 of miRD could be detected. Using this method, by obtaining miRD status, we could illustrate dynamic evolutionary process of a case with unique coincidence of ALL and LCH. Furthermore, we performed miRD detection using droplet digital PCR technology, and its sensitivity and quantitativity.

Research Products

• [Journal Article] Genomic analysis of clonal origin of Langerhans cell histiocytosis following acute lymphoblastic leukemia (2015)
  • Author(s): 2.Kato M, Seki M, Yoshida K, Sato Y, Oyama R, Arakawa Y, Kishimoto H, Taki T, Akiyama M, Shiraishi Y, Chiba K, Tanaka H, Mitsuiki N, Kajiwara M, Mizutani S, Sanada M, Miyano S, Ogawa S, Koh K, Takita J.
  • Journal Title: British Journal of Haematology Volume: Nov 5 Issue: 1 Pages: 169-172
  • DOI: 10.1111/bjh.13841
  • Peer Reviewed / Open Access / Acknowledgement Compliant