1. Fractionated photoimmunotherapy stimulates an anti-tumour immune response: an integrated mathematical and in vitro study.
- Author
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Zahid MU, Waguespack M, Harman RC, Kercher EM, Nath S, Hasan T, Rizvi I, Spring BQ, and Enderling H
- Subjects
- Humans, Female, Carcinoma, Ovarian Epithelial immunology, Carcinoma, Ovarian Epithelial therapy, Carcinoma, Ovarian Epithelial radiotherapy, Ovarian Neoplasms immunology, Ovarian Neoplasms therapy, Ovarian Neoplasms pathology, Ovarian Neoplasms radiotherapy, Cell Line, Tumor, T-Lymphocytes immunology, T-Lymphocytes radiation effects, Models, Theoretical, ErbB Receptors immunology, Immunotherapy methods, Photochemotherapy methods
- Abstract
Background: Advanced epithelial ovarian cancer (EOC) has high recurrence rates due to disseminated initial disease presentation. Cytotoxic phototherapies, such as photodynamic therapy (PDT) and photoimmunotherapy (PIT, cell-targeted PDT), have the potential to treat disseminated malignancies due to safe intraperitoneal delivery., Methods: We use in vitro measurements of EOC tumour cell and T cell responses to chemotherapy, PDT, and epidermal growth factor receptor targeted PIT as inputs to a mathematical model of non-linear tumour and immune effector cell interaction. The model outputs were used to calculate how photoimmunotherapy could be utilised for tumour control., Results: In vitro measurements of PIT dose responses revealed that although low light doses (<10 J/cm
2 ) lead to limited tumour cell killing they also increased proliferation of anti-tumour immune effector cells. Model simulations demonstrated that breaking up a larger light dose into multiple lower dose fractions (vis-à-vis fractionated radiotherapy) could be utilised to effect tumour control via stimulation of an anti-tumour immune response., Conclusions: There is promise for applying fractionated PIT in the setting of EOC. However, recommending specific fractionated PIT dosimetry and timing will require appropriate model calibration on tumour-immune interaction data in human patients and subsequent validation of model predictions in prospective clinical trials., (© 2024. The Author(s).)- Published
- 2024
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