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A Mathematical Model for Predicting Patient Responses to Combined Radiotherapy with CTLA-4 Immune Checkpoint Inhibitors.
Kim, Yongjin; Choe, Bo-Young; Suh, Tae Suk; Sung, Wonmo.
Afiliación
  • Kim Y; Department of Biomedical Engineering and of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
  • Choe BY; Department of Biomedical Engineering and of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
  • Suh TS; Department of Biomedical Engineering and of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
  • Sung W; Department of Biomedical Engineering and of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul 06591, Republic of Korea.
Cells ; 12(9)2023 05 03.
Article en En | MEDLINE | ID: mdl-37174706
ABSTRACT
The purpose of this study was to develop a cell-cell interaction model that could predict a tumor's response to radiotherapy (RT) combined with CTLA-4 immune checkpoint inhibition (ICI) in patients with hepatocellular carcinoma (HCC). The previously developed model was extended by adding a new term representing tremelimumab, an inhibitor of CTLA-4. The distribution of the new immune activation term was derived from the results of a clinical trial for tremelimumab monotherapy (NCT01008358). The proposed model successfully reproduced longitudinal tumor diameter changes in HCC patients treated with tremelimumab (complete response = 0%, partial response = 17.6%, stable disease = 58.8%, and progressive disease = 23.6%). For the non-irradiated tumor control group, adding ICI to RT increased the clinical benefit rate from 8% to 32%. The simulation predicts that it is beneficial to start CTLA-4 blockade before RT in terms of treatment sequences. We developed a mathematical model that can predict the response of patients to the combined CTLA-4 blockade with radiation therapy. We anticipate that the developed model will be helpful for designing clinical trials with the ultimate aim of maximizing the efficacy of ICI-RT combination therapy.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Cells Año: 2023 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Cells Año: 2023 Tipo del documento: Article