z-logo
open-access-imgOpen Access
Precise T cell recognition programs designed by transcriptionally linking multiple receptors
Author(s) -
Jasper Z. Williams,
Greg M. Allen,
Devan Shah,
Igal S. Sterin,
Ki H. Kim,
Vivian García,
Gavin E. Shavey,
Wei Yu,
Cristina Puig-Saus,
Jennifer Tsoi,
Antoni Ribas,
Kole T. Roybal,
Wendell A. Lim
Publication year - 2020
Publication title -
science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 12.556
H-Index - 1186
eISSN - 1095-9203
pISSN - 0036-8075
DOI - 10.1126/science.abc6270
Subject(s) - cancer immunotherapy , cancer cell , receptor , immunotherapy , chimeric antigen receptor , antigen , computational biology , biology , immune system , microbiology and biotechnology , cancer , immunology , genetics
Living cells often identify their correct partner or target cells by integrating information from multiple receptors, achieving levels of recognition that are difficult to obtain with individual molecular interactions. In this study, we engineered a diverse library of multireceptor cell-cell recognition circuits by using synthetic Notch receptors to transcriptionally interconnect multiple molecular recognition events. These synthetic circuits allow engineered T cells to integrate extra- and intracellular antigen recognition, are robust to heterogeneity, and achieve precise recognition by integrating up to three different antigens with positive or negative logic. A three-antigen AND gate composed of three sequentially linked receptors shows selectivity in vivo, clearing three-antigen tumors while ignoring related two-antigen tumors. Daisy-chaining multiple molecular recognition events together in synthetic circuits provides a powerful way to engineer cellular-level recognition.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom