Study Title: Parsing digital or analog TCR performance through piconewton forces
Study Title: Parsing digital or analog TCR performance through piconewton forces
Publication: Science Advances
Dana-Farber Cancer Institute authors: Aoi Akitsu, Kristine N. Brazin, Robert J. Mallis, Jonathan S. Duke-Cohan, Matthew A. Booker, Vincenzo Cinella, Jonathan Lee, Michael Y. Tolstorukov and Ellis L. Reinherz, MD
Summary:
Researchers at Dana-Farber Cancer Institute investigate new features of T cell performance, delineating a class of digital cytotoxic T lymphocytes (CTL) that are optimal in providing protection against virally infected or otherwise altered body cells, and by extension, most useful for immunotherapy. These digital performers are capable of recognizing and destroying altered cells expressing only a few copies of a target molecule. By leveraging these digital TCRs both for cancer vaccines and for cellular therapies, improvements in clinical outcomes of TCR-based therapies may result. The findings may also lead to new biomarkers for optimal adaptive immune recognition.
Significance:
Each T cell receptor (TCR) binds to a distinct peptide sitting in the groove of an MHC molecule (pMHC) arrayed on the surface of an antigen presenting cell. As motile T lymphocytes scan body tissues looking for aberrant cells including cancers in order to mediate their destruction, that detection and engagement places physical load on a single TCR-pMHC bond, tuning the TCR recognition of antigen in a highly specific manner. Yet at present, no force is applied when immuno-oncologists are testing performance of TCRs on T cells isolated from patients. That omission makes in vitro (i.e. in culture) measurement of TCR function unreliable as an in vivo proxy of T cell performance in the patient. This new understanding of TCR mechanobiology could lead to better immunotherapies, especially in targeting low-abundance tumor-specific antigens which are the most frequent type on cancer cells.
Funding:
This work was supported by NIH NIAID grants 1P01AI143565 and RO1 AI136301.
Contact: Nicole Oliverio, nicole_oliverio@dfci.harvard.edu
Journal
Science Advances
Article Title
Parsing digital or analog TCR performance through piconewton forces
Article Publication Date
14-Aug-2024
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