| Literature DB >> 30339020 |
Maria Soler1, Xiaokang Li1, Aurelian John-Herpin1, Julien Schmidt2, George Coukos2, Hatice Altug1.
Abstract
The screening and analysis of T cells functional avidity for specific tumor-associated antigens is crucial for the development of personalized immunotherapies against cancer. The affinity and kinetics of a T cell receptor (TCR) binding to the peptide-major histocompatibility complex (pMHC), expressed on tumor or antigen-presenting cells, have shown major implications in T cell activation and effector functions. We introduce an innovative methodology for the two-dimensional affinity analysis of TCR-pMHC in a label-free configuration by employing a multiparametric Surface Plasmon Resonance biosensor (MP-SPR) functionalized with artificial cell membranes. The biomimetic scaffold created with planar lipid bilayers is able to efficiently capture the specific and intact tumor-specific T cells and monitor the formation of the immunological synapse in situ. We have achieved excellent limits of detection for in-flow cell capturing, up to 2 orders of magnitude below the current state-of-the-art for plasmonic sensing. We demonstrate the accuracy and selectivity of our sensor for the analysis of CD8+ T cells bioengineered with TCR of incremental affinities specific for the HLA-A0201/NY-ESO-I157-165 pMHC complex. The study confirmed the significance of providing a biomimetic microenvironment, compared to the traditional molecular analysis, and showed fine agreement with previous results employing flow cytometry. Our methodology is reliable and versatile; thus, it can be applied to more sophisticated photonic and nanoplasmonic technologies for the screening of multiple cell types and boost the development of novel treatments for cancer.Entities:
Keywords: TCR affinity analysis; artificial cell membrane; cell capture; immunotherapy; lipid bilayer; real-time analysis; surface plasmon resonance
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Year: 2018 PMID: 30339020 DOI: 10.1021/acssensors.8b00523
Source DB: PubMed Journal: ACS Sens ISSN: 2379-3694 Impact factor: 7.711