Developing analysis tools of massively parallel cancer evolution simulation to understand intratumor heterogeneity

2018 Fiscal Year Final Research Report

• Project/Area Number: 17K12773
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Life / Health / Medical informatics
• Research Institution: The University of Tokyo
• Principal Investigator: Niida Atsushi 東京大学, 医科学研究所, 助教 (00772493)
• Project Period (FY): 2017-04-01 – 2019-03-31
• Keywords: シミュレーション

Outline of Final Research Achievements

Cancer is caused by an evolutionary process where a normal cell acquires mutations and is subject to natural selection. To understand the evolutionary process, we have performed a series of studies by employing cancer evolution simulation. In this study we developed a novel tools for sensitivity analysis, which examines how parameter values affect evolutionary dynamics. the novel tool, MASSIVE first performs massively parallel simulations on a super computer and then examines the results by an interactive visualization tool, MASSIVE viewer. As an example of an application of MASSIVE, we analyzed cancer evolution simulation on a dimensional lattice and found that spatial resource bias prompts branching evolution.

Free Research Field

計算生物学

Academic Significance and Societal Importance of the Research Achievements

本研究で開発した新しいパラメータ感受性解析手法 MASSIVEはこれまでの感受性解析手法とは全く異なる超並列計算と対話的可視化という二つの計算科学的技術を組み合わせ、幅広いパラメータ空間を直感的に探索可能にした点に新規性がある。我々はがんの進化シミュレーションの解析を目的に開発を行っているが、シミュレーション一般に応用可能な技術であり、感受性解析のデファクトスタンダードになると期待される。