A Mathematical Model for Predicting Patient Responses to Combined Radiotherapy with CTLA-4 Immune Checkpoint Inhibitors.
Yongjin KimBo-Young ChoeTae Suk SuhWonmo SungPublished in: Cells (2023)
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.
Keyphrases
- clinical trial
- combination therapy
- radiation therapy
- preterm infants
- early stage
- end stage renal disease
- single cell
- multiple sclerosis
- locally advanced
- open label
- newly diagnosed
- radiation induced
- randomized controlled trial
- ejection fraction
- peritoneal dialysis
- prognostic factors
- cross sectional
- study protocol
- cell therapy
- stem cells
- gestational age
- phase ii