面向临床前肿瘤免疫治疗大规模时空参数化与建模的 1000(+) 小鼠项目

Preclinical studies of chimeric antigen receptor (CAR)-T cell immunotherapies are often based on monitoring bioluminescent tumors implanted in mice to assess anti-tumor cytotoxicity.

Here, we introduce maRQup ( m urine a utomatic R adiance Q uantification and p arametrization), an easy-to-use method that automatically processes bioluminescent tumor images for quantitative analysis.

We demonstrate the ability of maRQup to analyze CAR-T cell treatments over >1000 tumor-bearing mice.

We compare CD19-targeting CAR-T cells comprising either a CD28 or a 4-1BB costimulatory domain, and found the former controlled the tumor burden better initially, while the latter reduced the frequency of tumor relapse.

We also applied maRQup to demonstrate faster tumor growth during the initial growth phase as compared to the relapse phase and to spatiotemporally analyze the high variability in immunotherapeutic control of tumors, based on their anatomical location. maRQup provides quantitative and statistically-robust insights on preclinical experiments that will contribute to the optimization of immunotherapies.