Background GPC3 chimeric antigen receptor T cell (CAR-T) therapy for liver cancer holds great promise. However, the effectiveness of CAR-T cells targeting a single antigen is limited due to the heterogeneous expression of the target antigen in liver cancer. To overcome this challenge, we present an innovative approach utilizing engineered T cells with dual targeting against two highly expressed antigens in liver cancer: cell surface GPC3 and intracellular AFP.
Methods In this study, we engineered GPC3 CAR-T cells (OriC101) to secrete a bispecific T cell engager (BiTE) composed of a TCR mimic antibody targeting AFP-MHC complex (OriA373). This BiTE specifically recognized the AFP-derived epitope (158–166) presented by the HLA-A02:01 molecule (figure 1). The secreted AFP BiTE effectively recruited and redirected both CAR-T cells and other CAR-T T cells towards the AFP/MHC complex on tumor cells.
Results Our findings revealed that the optimized GPC3 CAR-T cells secreting AFP-BiTE (OriC633–05) effectively activated both CAR-T cells and non-CAR-T cells while preserving a robust memory phenotype of CAR-T cells in vitro (figures 2 and 3). Moreover, OriC633–05 demonstrated significantly augmented anti-tumor activity against liver cancer cells with low GPC3 expression, both in vitro and in mouse tumor models (figure 4), surpassing the efficacy of GPC3 CAR-T cells and GPC3 CAR-T cells secreting alternative structures of AFP-BiTE.
Conclusions Hence, by leveraging dual orthogonal cytotoxic modalities with distinct specificities targeting surface and intracellular tumor-associated antigens, we have developed a promising strategy to overcome resistance to CAR-T cell therapy not only in liver cancer but also in other cancer types. Our results, demonstrating the superior activation and memory phenotype of GPC3 CAR-T cells secreting AFP-BiTE (OriC633–05), as well as its significantly enhanced anti-tumor activity against liver cancer cells with low GPC3 expression, and the potential for improved efficacy against liver cancer with high GPC3 expression, highlight the promising potential of this approach (figure 5).
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