Abstract
Animal models used to evaluate efficacies of immune checkpoint inhibitors are insufficient or inaccurate. We thus examined two xenograft models used for this purpose, with the aim of optimizing them. One method involves the use of peripheral blood mononuclear cells and cell line-derived xenografts (PBMCs-CDX model). For this model, we implanted human lung cancer cells into NOD-scid-IL2Rg-/- (NSI) mice, followed by injection of human PBMCs. The second method involves the use of hematopoietic stem and progenitor cells and CDX (HSPCs-CDX model). For this model, we first reconstituted the human immune system by transferring human CD34+ hematopoietic stem and progenitor cells (HSPCs-derived humanized model) and then transplanted human lung cancer cells. We found that the PBMCs-CDX model was more accurate in evaluating PD-L1/PD-1 targeted immunotherapies. In addition, it took only four weeks with the PBMCs-CDX model for efficacy evaluation, compared to 10-14 weeks with the HSPCs-CDX model. We then further established PBMCs-derived patient-derived xenografts (PDX) models, including an auto-PBMCs-PDX model using cancer and T cells from the same tumor, and applied them to assess the antitumor efficacies of anti-PD-L1 antibodies. We demonstrated that this PBMCs-derived PDX model was an invaluable tool to study the efficacies of PD-L1/PD-1 targeted cancer immunotherapies. Overall, we found our PBMCs-derived models to be excellent preclinical models for studying immune checkpoint inhibitors.