Analysis of minimal residual disease in ovarian cancer

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K18174
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 56040:Obstetrics and gynecology-related
• Research Institution: Keio University
• Principal Investigator: Masuda Kenta 慶應義塾大学, 医学部(信濃町), 助教 (30773460)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 卵巣癌 / 治療抵抗性 / 動物モデル

Outline of Final Research Achievements

In order to develop therapies that inhibit recurrence of ovarian cancer, it is necessary to elucidate the mechanism by which minimal residual disease after chemotherapy is resistant to treatment. With this research project, we developed a new ovarian cancer mouse model based on the organoid culture method, created an in vitro model of minimal residual disease, performed the spatial gene expression analysis using human ovarian cancer samples, and succeeded in identifying characteristic gene expression patterns in ovarian cancer minimal residual disease. By integrating these data, we obtained results that lead to the proposal of a new treatment strategy. Using the developed model animals, we will proceed with research and development toward the POC acquisition and the development of new therapeutic strategies.

Free Research Field

癌研究

Academic Significance and Societal Importance of the Research Achievements

本研究課題で開発した卵巣癌モデルマウスは、BRCA1/2遺伝子野生型の特徴を持ち、卵巣癌の中でも予後不良群を模倣している。BRCA1/2遺伝子野生型の特徴を有する卵巣癌は、既存の細胞障害性薬剤や分子標的薬への感受性が低く、アンメットメディカルニーズが高い。そのため今後非臨床試験を計画する上でも有用な動物モデルとなり得る。またオルガノイド培養法を応用して作成した微小残存病変モデルは、in vitroスクリーニングによる治療候補薬剤の同定が期待できる。またヒト卵巣癌検体に対して、空間的遺伝子発現解析の有用性を示したことにより、今後普遍的な卵巣癌MRDシグネチャの同定が期待できる。