Elucidation and challenge for the prediction of cancer clonal evolution and intra-tumor heterogeneity by computer simulation

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K12071
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: National Cancer Center Japan
• Principal Investigator: Kato Mamoru 国立研究開発法人国立がん研究センター, 研究所, 分野長 (40391916)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: がん細胞進化 / 計算機シミュレーション / 個別化医療 / がんゲノム医療

Outline of Final Research Achievements

We performed cancer-cell evolutionary simulations on VAF (variant allele frequency) data from a 73-year-old male colorectal cancer patient in the TCGA (Cancer Genome Atlas) database, and predicted that blocking APC, KRAS, and PIK3CA aberrations will have no effect on cancer-cell growth, but, when blocking TP53 aberrations, the metastatic cells will not grow (Nagornov and Kato, 2020). Then, we changed the data representation from cell-based to clone-based and achieved great computational speed-up (Nagornov, Nishino, and Kato, 2020). In addition to point mutations, we implemented a model that incorporates CNAs (copy number alterations) and tumor purity (manuscript in preparation).

Free Research Field

生物情報学

Academic Significance and Societal Importance of the Research Achievements

73歳大腸がん男性患者の実データを例に、遺伝子変異をNGS（次世代シークエンサー）で測定し、腫瘍内不均一性を考慮した数理シミュレーション・モデルを使って、個別化医療を実行する原理的可能性を、世界で初めて示した。どの遺伝子を遮断すればがん細胞が増殖しないか、数値シミュレーションで予測できる。これはすなわち、どの分子標的薬を使えば効果が見込めるかの、シミュレーションを用いた全く新しいタイプの個人化医療である。