Effectiveness of the combination of vascular targeted photodynamic therapy and anti-cytotoxic T-lymphocyte-associated antigen 4 in a preclinical mouse model of urothelial carcinoma Academic Article uri icon

Overview

MeSH Major

  • Magnetic Resonance Imaging
  • Prostatic Neoplasms

abstract

  • © 2019 The Japanese Urological Association Objective: To investigate the effectiveness of combination treatment of vascular targeted photodynamic therapy and anti-cytotoxic T-lymphocyte-associated antigen 4 immunotherapy in a mouse model of urothelial carcinoma. Methods: We used C57BL/6 mice injected with murine bladder 49 cell line. Mice were randomly allocated into four treatment groups: vascular targeted photodynamic therapy only, anti-cytotoxic T-lymphocyte-associated antigen 4 only, combination therapy and control. We carried out three separate experiments that used distinct cohorts of mice: tumor growth and development of lung metastases monitored with bioluminescent imaging (n = 91); survival evaluated with Kaplan–Meier curves (n = 111); and tumor cell population studied with flow cytometry (n = 20). In a fourth experiment, we re-challenged tumors in previously treated mice and compared tumor growth with that of naïve mice. Results: Combination therapy provided significant benefits over the other three treatment groups: prolonged survival (P < 0.0001), lower tumor signal (P < 0.0001) and decreased lung signal uptake (P ≤ 0.002). We also observed that mice previously treated with vascular targeted photodynamic therapy only or combination therapy did not present tumor growth after re-challenged tumors. Conclusions: Combination of vascular targeted photodynamic therapy with anti-cytotoxic T-lymphocyte-associated antigen 4 is an effective therapy in a urothelial carcinoma syngeneic mouse model. The present results suggest this therapy as a potential treatment option for both bladder and upper tract tumors in future clinical trials.

publication date

  • January 2019

Research

keywords

  • In Process

Identity

Digital Object Identifier (DOI)

  • 10.1111/iju.13878

Additional Document Info