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Published January 23, 2018 | Published + Supplemental Material
Journal Article Open

A kinetic investigation of interacting, stimulated T cells identifies conditions for rapid functional enhancement, minimal phenotype differentiation, and improved adoptive cell transfer tumor eradication

Abstract

For adoptive cell transfer (ACT) immunotherapy of tumor-reactive T cells, an effective therapeutic outcome depends upon cell dose, cell expansion in vivo through a minimally differentiated phenotype, long term persistence, and strong cytolytic effector function. An incomplete understanding of the biological coupling between T cell expansion, differentiation, and response to stimulation hinders the co-optimization of these factors. We report on a biophysical investigation of how the short-term kinetics of T cell functional activation, through molecular stimulation and cell-cell interactions, competes with phenotype differentiation. T cells receive molecular stimulation for a few minutes to a few hours in bulk culture. Following this priming period, the cells are then analyzed at the transcriptional level, or isolated as single cells, with continuing molecular stimulation, within microchambers for analysis via 11-plex secreted protein assays. We resolve a rapid feedback mechanism, promoted by T cell—T cell contact interactions, which strongly amplifies T cell functional performance while yielding only minimal phenotype differentiation. When tested in mouse models of ACT, optimally primed T cells lead to complete tumor eradication. A similar kinetic process is identified in CD8^+ and CD4^+ T cells collected from a patient with metastatic melanoma.

Additional Information

© 2018 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Received: October 25, 2017; Accepted: January 9, 2018; Published: January 23, 2018. Data Availability Statement: All RNA-seq data files are publicly available at https://www.ncbi.nlm.nih. gov/Traces/study/?acc=SRP126680, accession: PRJNA422284. Funding: This work was supported by National Cancer Institute, grant #'s: R01 CA170689, 5U54 CA119347, 1U54 CA199090-01, CA-16042, AI-28697; Jean Perkins Foundation; and Stand Up 2 Cancer SU2C-AACR-DT1012. The authors thank Georgi K. Marinov and Barbara Wold for valuable discussions and help on the analysis of the RNA-seq data, Igor Antoshechkin for technical support for performing RNA-seq in Millard and Muriel Jacobs Genetics and Genomics Laboratory at Caltech. We also thank Young Shik Shin and Chao Ma for the help on the initial stage of the experiments; Min Xue and Jun Wang for the help on preparing reagents; Julia B Sun for help on data acquisition, Siwen Hu-Lieskovan and Stephen Mok for suggestions for the mice experiments, and Kellin Haley for technical services for flow cytometry studies for human patient samples, which were performed in the UCLA Jonsson Comprehensive Cancer Center (JCCC) and Center for AIDS Research Flow Cytometry Core Facility.

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