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T cells expressing CD19-targeting chimeric antigen receptors (CARs) reveal high efficacy in the treatment of B cell malignancies. Here, we report that T cell receptor fusion constructs (TRuCs) comprising an antibody-based binding domain fused to T cell receptor (TCR) subunits can effectively reprogram an intact TCR complex to recognize tumor surface antigens. Unlike CARs, TRuCs become a functional component of the TCR complex. TRuC-T cells kill tumor cells as potently as second-generation CAR-T cells, but at significant lower cytokine release and despite the absence of an extra co-stimulatory domain. TRuC-T cells demonstrate potent anti-tumor activity in both liquid and solid tumor xenograft models. In several models, TRuC-T cells are more efficacious than respective CAR-T cells. TRuC-T cells are shown to engage the signaling capacity of the entire TCR complex in an HLA-independent manner.

Chimeric antigen receptor (CAR) T cells have been remarkably successful in patients with hematological malignancies expressing the CD19 surface antigen, but such level of success is far from being replicated in solid tumors. Engineered T cell receptor (TCR) T cells targeting cancer antigens were first developed over two decades ago and represent an alternative adoptive T cell approach that has produced provocative clinical data in solid cancers. However, several factors may hinder this technology from realizing its full potential, including the need for HLA matching, HLA downregulation by cancer cells, the suppressive tumor microenvironment, and tissue liabilities resulting from targeting antigens shared with normal tissues. Efforts therefore continue to engineer enhanced versions of CAR T and TCR T therapies that can overcome current barriers. Furthermore, emergent novel TCR-based, HLA-unrestricted platforms may also provide unique tools that integrate the complexity of the TCR signaling cascade that can be applied to treat solid tumors. This article reviews the current state of development of TCR T cell approaches and discusses next generation improvements to overcome their current limitations., (Copyright © 2019 Elsevier B.V. All rights reserved.)