Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model

• Project/Area Number: 16K10584
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Digestive surgery
• Research Institution: Osaka Medical College
• Principal Investigator: Yamamoto Kimiyo 大阪医科大学, 医学部, 非常勤講師 (70611078)
• Co-Investigator(Kenkyū-buntansha): 波江野 洋 国立研究開発法人国立がん研究センター, 先端医療開発センター, 特任研究員 (70706754) ; 内山 和久 大阪医科大学, 医学部, 教授 (80232867)
• Research Collaborator: INOUE Yoshihiro ; ISHII Masatsugu ; NAKAMURA Akira ; Michor Franziska ; MacArthur Ben D. ; Hur Chin
• Project Period (FY): 2016-04-01 – 2019-03-31
• Project Status: Completed (Fiscal Year 2018)
• Budget Amount: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000); Fiscal Year 2018: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000); Fiscal Year 2017: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000); Fiscal Year 2016: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
• Keywords: 数理モデル / 肝臓再生モデル / 肝再生モデル / 肝臓外科

Outline of Final Research Achievements

The paper published by the support from this grant adopted a combined clinical and theoretical approach for the goals of identifying successful/unsuccessful candidates for liver resection and monitoring post-hepatectomy liver regeneration. This translational approach was achieved by establishing a novel logistic growth framework with two carrying capacities of successful/unsuccessful liver regeneration. The study predicted whether the liver of a patient will succeed in recovering, with accuracies as high as 84-88% in both of a training cohort with cross validation and a separate validation cohort by utilizing the mathematical tool. We also proposed a powerful criteria to identify potential clinical predictors for successful liver resection and to predict the time course of liver regeneration.

Academic Significance and Societal Importance of the Research Achievements

当研究で出版した論文では、肝臓再生の定量的予測や術前の治療見込み予測を示唆できることを示した。これらの情報は、肝切除を要する症例の治療に当たって決定的因子であり、本研究の臨床還元によるインパクトは絶大である。また、当研究に適用された数理学分析手法は、生命現象の本質を数理モデルとして捉えるという目的で、生態学や水産学などといった様々な領域で応用されつつあるが、医学領域との融合は少ない。当研究成果は、数理学分析手法を医学に応用し医学の進歩へ新展開をもたらしたという学術的意義を持つ。また臨床現場にて、特殊な設備導入など必要とせず、しかも高い汎用性を持つ手法を開発した、という点で社会的意義を持つ。

Research Products

• [Int'l Joint Research] Harvard University/Massachusetts general hospital/Johns Hopkins University(米国)
• [Journal Article] KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance. (2018)
  • Author(s): Hinohara K, Wu HJ, Sebastien Vigneau, McDonald TO, Igarashi KJ, Yamamoto KN, Madsen T, Fassl A, Egri SB, Papanastasiou M, Ding L, Peluffo G, Cohen O, Kales SC, Lal-Nag M, Rai G, Maloney DJ, Jadhav A, Simeonov A, Wagle N, Brown M, Meissner A, Sicinski P, Jaffe JD, Jeselsohn R, Gimelbrant AA, Michor F, Polyak K.
  • Journal Title: Cancer Cell Volume: 34 Issue: 6 Pages: 939-953
  • DOI: 10.1016/j.ccell.2018.10.014
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] Mathematical modeling identifies optimum lapatinib dosing schedules for the treatment of glioblastoma patients (2018)
  • Author(s): Stein Shayna、Zhao Rui、Haeno Hiroshi、Vivanco Igor、Michor Franziska
  • Journal Title: PLOS Computational Biology Volume: 14 Issue: 1 Pages: e1005924-e1005924
  • DOI: 10.1371/journal.pcbi.1005924
  • Peer Reviewed / Open Access / Int'l Joint Research
• [Journal Article] Personalized Management of Pancreatic Ductal Adenocarcinoma Patients through Computational Modeling. (2017)
  • Author(s): Yamamoto KN, Yachida S, Nakamura A, Niida A, Oshima M, De S, Rosati LM, Herman JM, Iacobuzio-Donahue CA, Haeno H.
  • Journal Title: Cancer Res. Volume: 77 Issue: 12 Pages: 3325-3335
  • DOI: 10.1158/0008-5472.can-16-1208
  • Peer Reviewed / Int'l Joint Research
• [Journal Article] Personalized Management of Pancreatic Ductal Adenocarcinoma Patients Through Computational Modeling (2017)
  • Author(s): Kimiyo N Yamamoto, Shinichi Yachida, Akira Nakamura, Atsushi Niida, Minoru Oshima, Subhajyoti De, Lauren M Rosati, Joseph M. Herman, Christine A Iacobuzio-Donahue and Hiroshi Haeno
  • Journal Title: Cancer research Volume: ―
  • Peer Reviewed / Int'l Joint Research / Acknowledgement Compliant
• [Journal Article] Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model. (2016)
  • Author(s): Yamamoto KN Ishii M, Inoue Y, Hirokawa F, MacArthur BD, Nakamura A, Haeno H, Uchiyama K.
  • Journal Title: Scientific Reports Volume: 6 Issue: 1 Pages: 34214-34214
  • DOI: 10.1038/srep34214
  • Peer Reviewed / Open Access / Int'l Joint Research / Acknowledgement Compliant
• [Presentation] Personalized Management of Pancreatic Ductal Adenocarcinoma Patients through Computational Modeling. (2017)
  • Author(s): Kimiyo N. Yamamoto
  • Organizer: Physical Sciences in Oncology in US
  • Int'l Joint Research
• [Presentation] Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model. (2016)
  • Author(s): 山本君代
  • Organizer: Japan Society of Mathematical Biology
  • Place of Presentation: 九州大学(福岡県福岡市)
  • Year and Date: 2016-09-07
  • Invited