CD28 blockade controls T cell activation to prevent graft-versus-host disease in primates
Benjamin K. Watkins, … , Bernard Vanhove, Leslie S. Kean
Benjamin K. Watkins, … , Bernard Vanhove, Leslie S. Kean
Published August 13, 2018
Citation Information: J Clin Invest. 2018;128(9):3991-4007. https://doi.org/10.1172/JCI98793.
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Research Article Immunology Transplantation

CD28 blockade controls T cell activation to prevent graft-versus-host disease in primates

Abstract

Controlling graft-versus-host disease (GVHD) remains a major unmet need in stem cell transplantation, and new, targeted therapies are being actively developed. CD28-CD80/86 costimulation blockade represents a promising strategy, but targeting CD80/CD86 with CTLA4-Ig may be associated with undesired blockade of coinhibitory pathways. In contrast, targeted blockade of CD28 exclusively inhibits T cell costimulation and may more potently prevent GVHD. Here, we investigated FR104, an antagonistic CD28-specific pegylated-Fab′, in the nonhuman primate (NHP) GVHD model and completed a multiparameter interrogation comparing it with CTLA4-Ig, with and without sirolimus, including clinical, histopathologic, flow cytometric, and transcriptomic analyses. We document that FR104 monoprophylaxis and combined prophylaxis with FR104/sirolimus led to enhanced control of effector T cell proliferation and activation compared with the use of CTLA4-Ig or CTLA4-Ig/sirolimus. Importantly, FR104/sirolimus did not lead to a beneficial impact on Treg reconstitution or homeostasis, consistent with control of conventional T cell activation and IL-2 production needed to support Tregs. While FR104/sirolimus had a salutary effect on GVHD-free survival, overall survival was not improved, due to death in the absence of GVHD in several FR104/sirolimus recipients in the setting of sepsis and a paralyzed INF-γ response. These results therefore suggest that effectively deploying CD28 in the clinic will require close scrutiny of both the benefits and risks of extensively abrogating conventional T cell activation after transplant.

Authors

Benjamin K. Watkins, Victor Tkachev, Scott N. Furlan, Daniel J. Hunt, Kayla Betz, Alison Yu, Melanie Brown, Nicolas Poirier, Hengqi Betty Zheng, Agne Taraseviciute, Lucrezia Colonna, Caroline Mary, Gilles Blancho, Jean-Paul Soulillou, Angela Panoskaltsis-Mortari, Prachi Sharma, Anapatricia Garcia, Elizabeth Strobert, Kelly Hamby, Aneesah Garrett, Taylor Deane, Bruce R. Blazar, Bernard Vanhove, Leslie S. Kean

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Figure 7

Visualization of the blue gene module.

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Visualization of the blue gene module. (A) Visualization of gene coexpre...
(A) Visualization of gene coexpression network connections between the most connected genes in the blue module using Cytoscape. Shown are nodes with network connections whose topological overlap is above a threshold of 0.1. Edges with network connections above the threshold of 0.25 are shown. Mean expression fold change values of the FR104/sirolimus cohort versus HC for each gene are visualized using a false-color scale. Pathways were then identified using the DAVID database, using a cutoff derived from the Benjamini-Hochberg statistic. P < 0.05. In addition, 7 representative submodules containing genes from the top statistically ranking pathways (enumerated with the Reactome Database) are shown. (B) Functional distribution of all pathways enriched in the blue module. A complete list of the individual pathways identified is found in Supplemental Table 7. Pathway identification used a Benjamini-Hochberg–corrected P value of < 0.05.