In Vitro Tumor Cell-Binding Assay to Select High-Binding Antibody and Predict Therapy Response for Personalized64Cu-Intraperitoneal Radioimmunotherapy against Peritoneal Dissemination of Pancreatic Cancer: A Feasibility Study

Fukiko Hihara, Hiroki Matsumoto, Mitsuyoshi Yoshimoto, Takashi Masuko, Yuichi Endo, Chika Igarashi, Tomoko Tachibana, Mitsuhiro Shinada, Ming Rong Zhang, Gene Kurosawa, Aya Sugyo, Atsushi B. Tsuji, Tatsuya Higashi, Hiroaki Kurihara, Makoto Ueno, Yukie Yoshii

研究成果: Article査読

抄録

Peritoneal dissemination of pancreatic cancer has a poor prognosis. We have reported that intraperitoneal radioimmunotherapy using a64Cu-labeled antibody (64Cu-ipRIT) is a promising adjuvant therapy option to prevent this complication. To achieve personalized64Cu-ipRIT, we developed a new in vitro tumor cell-binding assay (64Cu-TuBA) system with a panel containing nine candidate64Cu-labeled antibodies targeting seven antigens (EGFR, HER2, HER3, TfR, EpCAM, LAT1, and CD98), which are reportedly overexpressed in patients with pancreatic cancer. We investigated the feasibility of64Cu-TuBA to select the highest-binding antibody for individual cancer cell lines and predict the treatment response in vivo for64Cu-ipRIT.64Cu-TuBA was performed using six human pancreatic cancer cell lines. For three cell lines, an in vivo treatment study was performed with64Cu-ipRIT using high-, middle-, or low-binding antibodies in each peritoneal dissemination mouse model. The high-binding antibodies significantly prolonged survival in each mouse model, while low-and middle-binding antibodies were ineffective. There was a correlation between in vitro cell binding and in vivo therapeutic efficacy. Our findings suggest that64Cu-TuBA can be used for patient selection to enable personalized64Cu-ipRIT. Tumor cells isolated from surgically resected tumor tissues would be suitable for analysis with the64Cu-TuBA system in future clinical studies.

本文言語English
論文番号5807
ジャーナルInternational journal of molecular sciences
23
10
DOI
出版ステータスPublished - 01-05-2022

All Science Journal Classification (ASJC) codes

  • 触媒
  • 分子生物学
  • 分光学
  • コンピュータ サイエンスの応用
  • 物理化学および理論化学
  • 有機化学
  • 無機化学

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