Integrated analysis for information derived from morphology and biological information of cultured synovial stem cells

2022 Fiscal Year Final Research Report

• Project/Area Number: 19K18453
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 56020:Orthopedics-related
• Research Institution: Tokyo Medical and Dental University
• Principal Investigator: Mizuno Mitsuru 東京医科歯科大学, 統合研究機構, プロジェクト助教 (00733908)
• Project Period (FY): 2019-04-01 – 2023-03-31
• Keywords: 再生医療実用化 / 画像解析

Outline of Final Research Achievements

Synovial stem cells, which we have administered in human clinical studies, are an excellent clinical cell source because they have high chondrogenic differentiation potential, are embryologically similar to other tissues in the knee joint. The purpose of this study is to construct a database integrating cell morphology information in culture phase contrast images of synovial stem cells and cell biology analyses such as proliferative and differentiation potential and gene expression profiles, and to attempt to improve manufacturing stability in the practical application of regenerative medicine technology. Cell images were continuously acquired and analyzed under various conditions. Moreover, we conducted deep learning to recognize cell images using a newly developed alternative to the phase contrast microscope, and achieved cell recognition accuracy equivalent to that of conventional methods such as cell counting by the chamber method and cell counting by fluorescent staining of cells.

Free Research Field

再生医療実用化

Academic Significance and Societal Importance of the Research Achievements

本研究は、代表者が実施している臨床用滑膜幹細胞の製造工程管理の簡便化を目指し、細胞の増殖性、特性を予測可能な画像解析技術を開発することを目的とし、細胞画像を用いた統合解析を行った。これまでに本研究課題を通して申請者が開発してきた画像解析技術(特開2021-193880、特開2022-173309)、本研究課題で取得する細胞形態に関するデータ、特性などの細胞生物学的な解析結果を統合し解析することで、主要因子を探索した。本研究は形態と機能を統合した科学的に根拠のある画像解析技術を開発し、再生医療の臨床現場で妥当性を検証することで実用性を高めることが可能であるなど、極めて学術的意義の高い研究である。