Adoptive T cell therapies have achieved significant clinical responses, especially in hematopoietic cancers. Two types of receptor systems have been used to redirect the activity of T cells, normal heterodimeric TCRs or synthetic chimeric Ag receptors (CARs). TCRs recognize peptide-HLA complexes whereas CARs typically use an Ab-derived single-chain fragments variable that recognizes cancer-associated cell-surface Ags. Although both receptors mediate diverse effector functions, a quantitative comparison of the sensitivity and signaling capacity of TCRs and CARs has been limited due to their differences in affinities and ligands. In this study we describe their direct comparison by using TCRs that could be formatted either as conventional αβ heterodimers, or as single-chain fragments variable constructs linked to CD3ζ and CD28 signaling domains or to CD3ζ alone. Two high-affinity TCRs (KD values of ∼50 and 250 nM) against MART1/HLA-A2 or WT1/HLA-A2 were used, allowing MART1 or WT1 peptide titrations to easily assess the impact of Ag density. Although CARs were expressed at higher surface levels than TCRs, they were 10–100-fold less sensitive, even in the absence of the CD8 coreceptor. Mathematical modeling demonstrated that lower CAR sensitivity could be attributed to less efficient signaling kinetics. Furthermore, reduced cytokine secretion observed at high Ag density for both TCRs and CARs suggested a role for negative regulators in both systems. Interestingly, at high Ag density, CARs also mediated greater maximal release of some cytokines, such as IL-2 and IL-6. These results have implications for the next-generation design of receptors used in adoptive T cell therapies.

Introduction of anticancer receptors, by gene transfer, into T cells has shown significant promise in the destruction of tumors (reviewed in Ref. 1). TCRs and chimeric Ag receptors (CARs) have both been used in this approach to target different classes of cell-surface cancer Ags (26). TCRs provide the opportunity to target intracellular Ags that are processed and presented by an MHC-encoded protein (7). CARs recognize cancer-associated cell-surface molecules using synthetic constructs that consist of a single-chain fragments variable (scFvs) with Ab variable domains linked to a transmembrane region and intracellular signaling domains (8).

Although TCR and CAR formats have some elements in common, the mechanistic details of signaling through CARs are less studied than TCRs (9, 10). The αβ TCR heterodimer assembles in a precisely controlled stoichiometry with the signaling machinery consisting of six CD3 subunits (CD3εγ, CD3εδ, CD3ζζ) (11). During peptide MHC (pepMHC) engagement by the TCR, the coreceptors CD4 or CD8 are brought into proximity with the TCR/CD3 complex. Efficient signaling of naive T cells also requires the action of costimulatory molecules such as CD28. Each of these cell surface molecules has evolved to provide exquisitely sensitive signaling capabilities that allow different T cell types to generate polyfunctional activities. In contrast, CARs continue to be developed with properties that not only differ from conventional TCRs but also vary in terms of Ag, Ag density, scFv affinity, scFv specificity, and signaling domains (12). Variability in signaling components not only includes the domains used but also the number and position of the signaling domains. First-generation CARs contained only the CD3ζ signaling domains, which were shown to mediate activity but lacked T cell persistence (13). Second-generation CARs, currently in use clinically, contain a costimulatory signal (typically either CD28 or 4-1BB) in tandem with the CD3ζ signaling domain (8, 14). Third-generation CARs have been developed that contain three domains and provide further diversity in which signaling pathways are incorporated into CAR activation of T cells (15). Although most CARs contain scFv fragments as Ag-recognition domains, alternative receptor constructs such as designed ankyrin repeat proteins are in development (16).

Although much has been learned about the sensitivity and mechanics of TCR-mediated signaling, direct comparison with the functional properties of CARs has been a challenge as there are multiple components that differ between TCRs and CARs. In principle, one could compare a CAR construct that binds to a pepMHC complex (reviewed in Ref. 17) with a TCR that binds to the same pepMHC, but even these comparisons differ in receptor binding affinity and specificity. For example, recent efforts used an Ab called ESK1 that has high affinity (KD = 0.2 nM) for the WT1/HLA-A2 complex (18). This Ab was tested for activity and toxicity in mice as a soluble Fc containing Ab, as a bispecific molecule, and a CAR (1921). However, recent crystallographic studies showed that the ESK1 Ab docked over the N terminus of the WT1 peptide, with atomic interactions limited to the first four peptide residues, thus explaining why ESK1 cross-reacted with other human peptides that shared these residues such as the peptide PIGQ (22). Because the ESK1 Ab lacks specificity for WT1 peptide, it is unlikely to be applied in more sensitive therapeutic approaches, such as adoptive T cell therapies.

Even if a TCR-like Ab has the same specificity as a TCR, the direct comparison of TCR and CAR formats would be difficult, as they would no doubt differ substantially in affinity. Abs typically bind their ligands with KD in the nanomolar range, whereas TCRs typically bind pepMHC with KD values in the micromolar range (23). Recently a comparison of TCR and CAR sensitivities was carried out using a naturally occurring TCR and an scFv, both of which bind to WT1/HLA-A2 (24). Differences in functional activity and specificity were observed between the TCR and CAR but it remained to be determined whether these were attributable to differences in affinity, specificity (of the TCR versus the scFv), coreceptor involvement or expression levels of the two constructs. To more effectively compare the two receptors, we previously developed a CAR consisting of the α and β variable domains from a high-affinity murine TCR tethered to intracellular signaling domains typically used with CARs (25). This CAR construct had a decrease in sensitivity compared with its conventional TCR counterpart; however, it was still capable of directing the activity of CD8 and CD4 T cells against a B16-SIY tumor, in which the SIY peptide was upregulated.

To explore further the details of TCR- and CAR-mediated T cell activity, we have developed human TCR systems against the two cancer Ags, WT1 and MART1. The WT1 Ag has been identified as a top target for cancer immunotherapies (26) and trials have been initiated to target this Ag (27), whereas the MART1 Ag is one of the most studied targets for adoptive T cell therapies (28, 29). In this study we describe a comparison of TCRs to CARs using nanomolar affinity receptors for the WT1/HLA-A2 or MART1/HLA-A2 complexes. In both cases TCRs from T cell clones, isolated from a patient’s peripheral lymphocytes, were engineered in a single-chain TCR (Vβ-linker-Vα) format by yeast display to bind with high affinity to WT1/HLA-A2 (described in this report) or MART1/HLA-A2 (30). This allowed the stabilized single-chain TCR molecules to be reconstituted as a conventional full-length TCR or as a CAR construct that contained T cell intracellular signaling domains as now used in clinical trials with CD19-directed CARs and other CARs (9).

Engineering of the two single-chain TCRs against MART1/HLA-A2 or WT1/HLA-A2 to affinities (KD values of ∼50 and 250 nM) in the same range as many scFv fragments used in CARs allowed us to directly compare the activity mediated by a conventional TCR and a CAR, and to do so in the absence of the coreceptor CD8. CAR constructs exhibited 10–100-fold reductions in sensitivity to their respective pepHLA-A2 complexes, as compared with the conventional TCR (αβ variable and constant domains). This lower sensitivity was despite higher surface expression of the CAR relative to the TCR. Reductions in sensitivity were observed with both first-generation (CD3ζ signaling domain only) and second-generation (CD28/CD3ζ signaling domains) CARs. These sensitivity values were observed even in the absence of the CD8 coreceptor, indicating that the TCR/CD3 machinery itself accounts for the differences (10, 12). Mathematical modeling suggested that the CAR result could be explained by either a 1000-fold reduction in the kinetic proofreading rate (kp) or by a 100-fold reduction in the activation rate (Kact, i.e., conversion of intracellular substrate to product), or by a combination of these mechanisms. Moreover, the CAR and TCR constructs appeared to differ in the maximal amount of some cytokines released at higher Ag densities. For example, the CAR construct stimulated both CD8 and CD4 T cells to secrete 1.5–2-fold higher levels of IL-6 than the TCR construct. Direct comparisons of normal TCR-mediated effects versus CAR-mediated effects, using the identical recognition machinery, should allow a greater understanding of next-generation CAR formats, their sensitivities, and the influence of Ag-density on cancer cells (e.g., from different patients, or within the same patient) (8).

WT1 peptide (RMFPNAPYL) and the WT1 structurally similar peptide PIGQ (RMFPGEVAL) were synthesized by Genscript (Piscataway, NJ). MART1 peptide (ELAGIGILTV) was synthesized by standard F-moc chemistry at the Macromolecular Core Facility at Penn State University College of Medicine (Hershey, PA). T cells were stained with various concentrations of refolded HLA-A2–biotin and AAD-biotin. HLA-A2–biotin was refolded in complex with an ultraviolet-cleavable peptide, which was exchanged with the desired peptide in excess by exposure to UV light for >30 min (31). To generate HLA-A2 tetramer, HLA-A2–biotin monomer was incubated at a 4:1 ratio with streptavidin-PE (BD Biosciences). Abs used to detect expression of TCRs on surface of T cells included: anti-TCR Vβ3.1 (Thermo Fisher Scientific), PE streptavidin (BD Pharmingen), and Alexa Fluor 647 F(ab′)2 fragment of goat anti-mouse IgG (H+L) (Life Technologies).

The D13.1.1 and T1 full-length TCR genes [human variable domains, murine constant domains containing engineered C region cysteines (32)] and D13.1.1-CAR and T1-CAR genes (human variable domains linked to murine CD28 and CD3ζ) and first-generation D13.1.1-CAR (human variable domains linked to murine CD3ζ) were synthesized by GenScript. The D13.1.1 and T1 full-length genes were cloned into the pMP71 vector using NotI and EcoRI restriction sites (33). The D13.1.1-CAR and T1-CAR genes were cloned in the pMP71 vector using NotI and SalI restriction sites. Plat-E cells were plated at a concentration of 1 × 106 cell per well (six-well plate) in DMEM media with added puromycin and blasticidin. After 24 h, ∼30 μg of DNA was transfected into Plat-E cells and retroviral particles were harvested 48 h posttransfection. CD8 and CD4 T cells were harvested from AAD transgenic mice using a CD4 and CD8 mouse untouched T cells Dynabead kit (Thermo Fisher Scientific). T cells were activated with anti-CD28 and anti-CD3 beads (Thermo Fisher Scientific) and 30 U/ml of recombinant mouse IL-2 (Roche) for 24 h. Then 1 × 106 T cells were added to 1 ml of filtered (0.45 μm) retroviral supernatant with 50 μl of Lipofectamine 2000 (Life Technologies) per 6 ml of retroviral supernatant and an additional 30 U/ml of recombinant IL-2. The cells were spinfected by spinning at 800 × g for 1 h in the presence of IL-2. Cells were then incubated at 37°C for 72 h. After 48 h, T cells were split 1:2 in IMDM.

For activation assays, 7.5 × 104 T cells were incubated with 7.5 × 104 T2 cells (HLA-A2+) and various concentrations of peptide in a final volume of 200 μl (96-well plate) for 24 h. Next, 50 μl of supernatants were assayed for IFN-γ using mouse IFN-γ ELISA Ready-SET-Go kit (eBioscience). To detect IL-2, IL-6, IL-10, MIP-1β, and TNF-α the Luminex Multiplex kit was used (Millipore) according to the manufacturer’s protocol. For IL-2 detection from transduced 58−/− cells, 2HB 96-well flat-bottom plates were coated with 50 μl of 2.5 mg/ml anti-murine IL-2 (BD Pharmingen) in 0.1 M Na2HPO4 (pH = 9) overnight at 4°C. Next, 50 μl of supernatants were incubated in coated plates, followed by diluted (1:200) biotinylated anti-murine IL-2 (BD Pharmingen), followed by streptavidin-HRP (BD Pharmingen) diluted 1:10,000. Finally, TMB substrate (KPL) was added to each well until a color change occurred. The reaction stopped by adding 1 N H2SO4 and the absorbance was read at 450 nm.

The following ordinary differential equations were used for the kinetic proofreading model:

Lt=konLR+koff(C0+C1)
Rt=konLR+koff(C0+C1)
C0t=konLRkoffC0kpC0
C1t=kpC0koffC1
Pt=KactC1(PTP)γP

where kon and koff are the TCR-pepHLA kinetic rate constants, kp is the kinetic proofreading rate, Kact is the downstream activation rate, and γ is the background deactivation rate. The output of the model is P, which represents the active state of a downstream molecule (e.g., product of a reaction) with the total amount denoted as PT. We obtained the following steady-state solution to this system:

C1=kpkoffRT+LT+koffkon(RT+LT+koffkon)24RTLT2
P^=KactC1KactC1+γ

The model was modified to incorporate the incoherent feedforward loop with the following equations:

Yt=KactC1(YTY)φY
Pt=λY(PTP)βC1

where φ is the background deactivation rate of Y, λ is the Kact of P by Y, and β is the inhibition rate of P by C1. This changes the steady-state solution to:

Y^=KactC1KactC1+φ
P^=λYλY+βC1+γ

Active concentrations in the steady state equations are expressed as nondimensionalized fractions Y^=YYT, and P^=PPT. Some calculations were generated using γ = 1, kon = 10−6, koff = 10−1, kp = 1, RT = 3 × 104, Kact = 1 or the indicated parameters. Calculations in Fig. 5D used the following modified parameters: β = 1, φ = 1, kp = 10−2, Kact = 1.

Comparisons between various data outputs measured for TCRs and CARs were statistically analyzed using GraphPrism 6 software, with either a Student t test (for single comparisons) or with a one-way ANOVA and Tukey posttest (for multiple comparisons). Significance was accepted at p < 0.05.

To engineer a TCR that could operate independent of coreceptor and that could be used in a scFv-like format with affinity in the range of standard CARs, we used the yeast display system to improve the affinity of a TCR isolated from a CD8+ T cell clone raised against WT1/HLA-A2. The single-chain TCR consisted of the TCR Vβ domain linked to the Vα domain and fused to the AGA2 surface protein, with an N-terminal hemagglutinin (HA) tag and a C-terminal c-myc tag (Fig. 1A). Although HA and c-myc were detected on the surface of yeast, an anti-Vβ3 Ab did not detect the fusion protein (Fig. 1B), most likely because the V domains are not stable as a single-chain without select mutations (34, 35). To isolate a stabilized scFv form, a yeast display library of the hypermutated single-chain construct was generated by error-prone PCR, and the library was selected using FACS for Vβ3 expression. A TCR clone, called D13, was isolated, which expressed a positive population when stained with the anti-Vβ3 Ab (Fig. 1B).

FIGURE 1.

Isolation of a high-affinity single-chain TCR against WT1/HLA-A2. (A) Schematic of the single-chain TCR construct in the yeast display system. (B) The wild-type TCR (template) was engineered for improved stability and higher affinity on the surface of yeast as a single-chain TCR. Staining of the template (first column), a stabilized TCR called D13 (second column), and a high-affinity TCR called D13.1.1 (third column) is shown. The constructs are stained for expression with an Ab against the HA epitope (first row), anti-Vβ3 (second row), or WT1/HLA-A2-Ig dimer (third row). Staining of template (first column), a stabilized TCR called D13 (second column), and a high-affinity TCR called D13.1.1 (third column) is shown. Gray filled histogram represents secondary only controls. (C) The high-affinity D13.1.1-TCR displayed on yeast was stained with various concentrations of biotinylated WT1/HLA-A2 monomer, followed by streptavidin-PE secondary. (D) Mean fluorescence intensity (MFI) values of histograms from (C) were plotted versus WT1/HLA-A2 monomer concentration. The calculated ED50 value is indicated. (E) CD8+ T cells from AAD mice were transduced with the D13.1.1 TCR, and cells were incubated with T2 cells (HLA-A2+) at a ratio of 1:1, in the presence of various concentrations of the WT1 peptide (RMFPNAPYL) or PIGQ peptide (RMFPGEVAL). Supernatants were assayed for IFN-γ by ELISA.

FIGURE 1.

Isolation of a high-affinity single-chain TCR against WT1/HLA-A2. (A) Schematic of the single-chain TCR construct in the yeast display system. (B) The wild-type TCR (template) was engineered for improved stability and higher affinity on the surface of yeast as a single-chain TCR. Staining of the template (first column), a stabilized TCR called D13 (second column), and a high-affinity TCR called D13.1.1 (third column) is shown. The constructs are stained for expression with an Ab against the HA epitope (first row), anti-Vβ3 (second row), or WT1/HLA-A2-Ig dimer (third row). Staining of template (first column), a stabilized TCR called D13 (second column), and a high-affinity TCR called D13.1.1 (third column) is shown. Gray filled histogram represents secondary only controls. (C) The high-affinity D13.1.1-TCR displayed on yeast was stained with various concentrations of biotinylated WT1/HLA-A2 monomer, followed by streptavidin-PE secondary. (D) Mean fluorescence intensity (MFI) values of histograms from (C) were plotted versus WT1/HLA-A2 monomer concentration. The calculated ED50 value is indicated. (E) CD8+ T cells from AAD mice were transduced with the D13.1.1 TCR, and cells were incubated with T2 cells (HLA-A2+) at a ratio of 1:1, in the presence of various concentrations of the WT1 peptide (RMFPNAPYL) or PIGQ peptide (RMFPGEVAL). Supernatants were assayed for IFN-γ by ELISA.

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As expected, due to the well-known low affinity of TCRs for cancer pepMHC Ags (36), binding to WT1/HLA-A2 dimers by this TCR was not detected (Fig. 1B). The anti-Vβ3–stabilized TCR was subsequently engineered for enhanced affinity by generating a library in the CDR1α domain, which was sorted for binding to WT1/HLA-A2. A clone with weak but positive reactivity (D13.1) was subsequently used as a template for CDR3β libraries, followed by further rounds of FACS for binding to WT1/HLA-A2. TCR clone D13.1.1 showed a significant increase in binding to WT1/HLA-A2 dimers (Fig. 1B). Based on titrations with soluble WT1/HLA-A2 monomers, we estimated the D13.1.1 TCR exhibited a KD of ∼250 nM (Fig. 1C, 1D).

Given that the Ab that binds to WT1/HLA-A2, called ESK1, also bound to peptides that shared the same N-terminal residues as the WT1 peptide (22), the PIGQ (RMFPGEVAL) peptide was tested for activity against the D13.1.1 TCR. Tetramers of the PIGQ peptide/HLA-A2 did not bind to the D13.1.1 TCR (data not shown), nor did the PIGQ peptide stimulate CD8 T cells that expressed the D13.1.1 TCR (Fig. 1E). Furthermore, the CD8+ T cells did not exhibit high basal levels of activity as would be observed with self-peptide reactivity seen with some higher-affinity TCRs (37, 38).

In addition to the single-chain TCR against WT1/HLA-A2, we recently described the engineering of an analogous TCR called T1 against MART1/HLA-A2 with a KD value of ∼50 nM for the MART1 10-mer, ELAGIGILTV (30). These two TCR systems provided independent reagents to compare TCR and CAR formats. The Vα and Vβ domains were each formatted in two constructs, a TCR that contained the full-length human V regions linked to mouse C regions, and a CAR in which the Vα and Vβ variable domains were linked to a CD8 hinge, a CD28 transmembrane region, and the CD28 and CD3ζ intracellular signaling domains (Fig. 2A).

FIGURE 2.

Activity of D13.1.1 and T1 TCR and CAR constructs in 58−/− cells. (A) Schematic of the TCR and CAR constructs used for the D13.1.1 and T1 TCRs. (B) The 58−/− cells transduced with the D13.1.1 TCR or CAR were stained with 50 nM WT1/HLA-A2 tetramer. Cells were also titrated with different concentrations of WT1/HLA-A2 monomer and mean fluorescence intensity (MFI) values for each concentration were used to calculate percent bound, using the MFI from the highest concentration of monomer as 100%. (C) Same as in (B) except the T1 TCR against MART1/HLA-2 was used. (D) Transduced cells with the D13.1.1 or T1 TCRs were incubated with T2 cells (HLA-A2+) at a 1:1 ratio and various concentrations of WT1 or MART1 peptides, respectively. Supernatants were then assayed for IL-2 concentrations by ELISA (n = 2). (E) The average log of MFI from two separate staining experiments is shown and the SE of the average is represented with error bars (p = 0.04 for D13.1.1 TCR versus CAR MFI values, p = 0.09 for T1 TCR versus CAR MFI values). Additionally, the EC50 values from two separate IL-2 activation experiments were plotted and the SE is shown with error bars (p = 0.09 for D13.1.1 TCR versus CAR EC50 values, p = 0.1 for T1 TCR versus CAR EC50 values). The asterisk (*) indicates statistical significance (p < 0.05) determined using Student t test in GraphPad Prism 6.

FIGURE 2.

Activity of D13.1.1 and T1 TCR and CAR constructs in 58−/− cells. (A) Schematic of the TCR and CAR constructs used for the D13.1.1 and T1 TCRs. (B) The 58−/− cells transduced with the D13.1.1 TCR or CAR were stained with 50 nM WT1/HLA-A2 tetramer. Cells were also titrated with different concentrations of WT1/HLA-A2 monomer and mean fluorescence intensity (MFI) values for each concentration were used to calculate percent bound, using the MFI from the highest concentration of monomer as 100%. (C) Same as in (B) except the T1 TCR against MART1/HLA-2 was used. (D) Transduced cells with the D13.1.1 or T1 TCRs were incubated with T2 cells (HLA-A2+) at a 1:1 ratio and various concentrations of WT1 or MART1 peptides, respectively. Supernatants were then assayed for IL-2 concentrations by ELISA (n = 2). (E) The average log of MFI from two separate staining experiments is shown and the SE of the average is represented with error bars (p = 0.04 for D13.1.1 TCR versus CAR MFI values, p = 0.09 for T1 TCR versus CAR MFI values). Additionally, the EC50 values from two separate IL-2 activation experiments were plotted and the SE is shown with error bars (p = 0.09 for D13.1.1 TCR versus CAR EC50 values, p = 0.1 for T1 TCR versus CAR EC50 values). The asterisk (*) indicates statistical significance (p < 0.05) determined using Student t test in GraphPad Prism 6.

Close modal

The TCR and CAR constructs were transduced into the murine 58−/− T cell hybridoma cell line (coreceptor and TCR αβ negative) and positive populations of cells were selected by FACS for binding to their respective pepHLA-A2 (Fig. 2B, 2C). Transductions of the 58−/− cell line allowed us to compare receptor levels and pepHLA-A2 sensitivity independent of the influence of coreceptor or endogenous α and β TCRs. Staining with a saturating concentration of pepHLA-A2 tetramer showed that in both cases the CAR was expressed at ∼10-fold higher surface levels than the conventional TCR (Fig. 2B, 2C, left panels). These differences in the levels of TCRs versus CARs were also verified by staining with the anti-Vβ Abs for each TCR (data not shown).

To determine if the TCR and CAR constructs bound with similar affinities, the T cells with transduced TCRs and CARs were titrated with their respective pepHLA-A2 monomers (biotinylated), washed, and stained with streptavidin-PE (Fig. 2B, 2C, right panels). Because of the differences in total cell surface levels of TCRs and CARs, the binding was adjusted for maximum levels at the highest pepHLA-A2 monomer concentration. The binding curves for the TCR and CAR in both systems were similar, with 50% maximal binding concentrations (estimated KD values) within 2-fold.

To assess peptide-specific stimulatory capacity, T cell hybridoma lines expressing the TCR and CAR constructs were incubated with T2 cells (HLA-A2+) and exogenously added peptides, and secreted IL-2 was measured (Fig. 2D). For both D13.1.1 and T1, the full-length TCR was ∼10-fold more sensitive to pepMHC than their respective CAR constructs, despite the CAR expression at significantly higher surface levels. The reciprocal relationship between surface levels and sensitivity can be seen for both the WT1 and MART1 systems (Fig. 2E).

To determine if the expression level and sensitivity differences between CARs and TCRs were observed in primary cells, CD8 and CD4 T cells from AAD mice (HLA-A2α1/α2 with Dbα3) were transduced with D13.1.1 TCR and CAR constructs. Transduced cells were stained with WT1/HLA-A2 tetramer and anti-Vβ3 Ab (Fig. 3A). The CAR construct was expressed at similar surface levels in CD8 and CD4 T cells compared with the conventional TCR (Fig. 3B). The expression levels of the TCR consistently seemed more homogenous among the population, compared with CARs that exhibited a broader peak. The heterogeneity of surface levels of receptors expressed among individual T cells can be quantified by determining the coefficient of variation (CV) value, which is a measure of the broadness of stained population (i.e., peak). When stained with WT1/HLA-A2 tetramer, the D13.1.1 TCR peak had CV values of 65 and 76 in CD8 and CD4 T cells respectively, whereas the D13.1.1 CAR peak had CV values of 84 and 117 in CD8 and CD4 T cells, respectively (Fig. 3B). The higher CV value is indicative of greater variation between cells in their individual expression of the CAR receptor. Higher variation of CAR surface levels compared with full-length TCR levels was also observed using the T1 system in CD4 T cells (Supplemental Fig. 1A, 1B).

FIGURE 3.

Flow cytometry and binding analysis of D13.1.1 TCR and CAR constructs transduced in primary CD8 and CD4 T cells. (A) CD8 and CD4 T cells were isolated from AAD mice, activated in vitro with anti-CD3/CD28 beads, and transduced with D13.1.1 TCR and CAR constructs. Transduced cells were stained with 50 nM WT1/HLA-A2 tetramer and anti-Vβ3 Ab. Viable cells were gated based on a forward scatter versus side scatter plot. (B) The median fluorescence intensity (MFI) and CV values were calculated for the TCR and CAR constructs in CD8 and CD4 transduced cells [CD8 n = 2, p = 0.6 (MFI), 0.01 (CV), CD4 n = 4, p = 0.2 (MFI), 0.003 (CV)]. (C) Transduced CD4 cells were titrated with WT1/HLA-A2 monomer (left) and tetramer (right). Percent maximum binding (100% set at highest concentration stained) was plotted against concentration of monomer and tetramer respectively. The asterisk (*) indicates statistical significance (p < 0.05) determined using Student t test in GraphPad Prism 6.

FIGURE 3.

Flow cytometry and binding analysis of D13.1.1 TCR and CAR constructs transduced in primary CD8 and CD4 T cells. (A) CD8 and CD4 T cells were isolated from AAD mice, activated in vitro with anti-CD3/CD28 beads, and transduced with D13.1.1 TCR and CAR constructs. Transduced cells were stained with 50 nM WT1/HLA-A2 tetramer and anti-Vβ3 Ab. Viable cells were gated based on a forward scatter versus side scatter plot. (B) The median fluorescence intensity (MFI) and CV values were calculated for the TCR and CAR constructs in CD8 and CD4 transduced cells [CD8 n = 2, p = 0.6 (MFI), 0.01 (CV), CD4 n = 4, p = 0.2 (MFI), 0.003 (CV)]. (C) Transduced CD4 cells were titrated with WT1/HLA-A2 monomer (left) and tetramer (right). Percent maximum binding (100% set at highest concentration stained) was plotted against concentration of monomer and tetramer respectively. The asterisk (*) indicates statistical significance (p < 0.05) determined using Student t test in GraphPad Prism 6.

Close modal

To measure the binding of the TCR and CAR receptors, transduced CD4 and CD8 T cells were titrated with WT1/HLA-A2 monomer and tetramer (Fig. 3C). Binding curves were similar, but shifted ∼2-fold for the CAR (i.e., 2-fold higher affinity or avidity for the CAR). Thus, if anything, the CAR had a slightly greater affinity for the WT1/HLA-A2 Ag.

The sensitivity of the CAR and TCR constructs was tested by incubating transduced CD4 and CD8 T cells with T2 cells and various concentrations of WT1 peptide. Supernatants were analyzed for IFN-γ by ELISA, and for a panel of cytokines using the Luminex Multiplex system (CD8 T cells, Fig. 4A; CD4 T cells, Fig. 4B). As with 58−/− cells, cells expressing the conventional TCR were nearly 100-fold more sensitive to WT1/HLA-A2 than cells expressing the CAR construct, for each of the cytokines examined (Fig. 4C, 4D). It was also notable that for those cytokines where sensitivity was sufficiently high to reveal full concentration curves, the highest concentrations of peptide Ag yielded reduced cytokine levels. Similar peptide-titration curves have been seen in many studies with TCR-mediated activities, and it has been predicted that high-antigen inhibition is due to a state of negative regulation by Src homology 2 domain phosphatase-1 (SHP-1) (39, 40). As such, our results suggest that both TCRs and CARs exhibit the potential for negative regulation at high Ag density.

FIGURE 4.

Binding and activity of D13.1.1 TCR and CAR constructs in primary CD8 and CD4 T cells. (A and B) Transduced AAD CD8 (A) and CD4 (B) T cells were incubated with T2 cells (HLA-A2+) at a 1:1 ratio and various concentrations of WT1 peptide. Supernatants were assayed for IFN-γ concentrations by ELISA. IL-2, IL-6, IL-10, MIP-1β, and TNF-α concentrations were calculated using the Luminex Multiplex system. (C and D) EC50 values from three separate experiments with CD8 [p = 0.2 (IL-2), p = 0.3 (IL-6), p = 0.2 (IL-10), p = 0.08 (MIP-1β), p = 0.002 (TNF-α), p < 0.0001 (IFN-γ)] (C) and five separate experiments with CD4 [p = 0.3 (IL-2), p = 0.04 (IL-6), p = 0.001 (IL-10), p < 0.0001 (MIP-1β), p = 0.002 (TNF-α), p = 0.02 (IFN-γ)] (D) T cells were calculated for each cytokine and plotted with the SE represented with error bars. (E and F) The maximum concentration of each cytokine released for the CAR was calculated relative to the respective maximum concentration for the TCR. Values were adjusted to account for differences in transduction efficiency between TCR and CAR. The average ratios from three separate experiments with CD8 T cells (p = 0.5 for IL-2 versus IL-6, p = 0.9 for IL-2 versus IL-10, p = 0.9 for IL-2 versus TNF-α, p = 0.7 for IL-2 versus IFN-γ, p = 0.05 for IL-6 versus IL-10, p = 0.1 for IL-6 versus TNF-α, p = 0.1 for IL-6 versus IFN-γ, p = 0.9 for IL-10 versus TNF-α, p = 0.9 for IL-10 versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ). For MIP-1β, n = 1 due to saturation at high ligand concentrations (E) and five separate experiments with CD4 T cells (p = 0.07 for IL-2 versus IL-6, p = 0.9 for IL-2 versus IL-10, p = 0.9 for IL-2 versus MIP-1β, p = 0.9 for IL-2 versus TNF-α, p = 0.9 for IL-2 versus IFN-γ, p = 0.07 for IL-6 versus IL-10, p = 0.03 for IL-6 versus MIP-1β, p = 0.007 for IL-6 versus TNF-α, p = 0.02 for IL-6 versus IFN-γ, p = 0.9 for IL-10 versus MIP-1β, p = 0.9 for IL-10 versus TNF-α, p = 0.9 for IL-10 versus IFN-γ, p = 0.9 for MIP-1β versus TNF-α, p = 0.9 for MIP-1β versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ) (F) are plotted with error bars representing the SE. The asterisk (*) indicates statistical significance (p < 0.05) determined using Student t test (EC50) or one-way ANOVA followed by Tukey test (maximum cytokine ratios) in GraphPad Prism 6. The p values generated from the Tukey test are adjusted for multiple comparisons.

FIGURE 4.

Binding and activity of D13.1.1 TCR and CAR constructs in primary CD8 and CD4 T cells. (A and B) Transduced AAD CD8 (A) and CD4 (B) T cells were incubated with T2 cells (HLA-A2+) at a 1:1 ratio and various concentrations of WT1 peptide. Supernatants were assayed for IFN-γ concentrations by ELISA. IL-2, IL-6, IL-10, MIP-1β, and TNF-α concentrations were calculated using the Luminex Multiplex system. (C and D) EC50 values from three separate experiments with CD8 [p = 0.2 (IL-2), p = 0.3 (IL-6), p = 0.2 (IL-10), p = 0.08 (MIP-1β), p = 0.002 (TNF-α), p < 0.0001 (IFN-γ)] (C) and five separate experiments with CD4 [p = 0.3 (IL-2), p = 0.04 (IL-6), p = 0.001 (IL-10), p < 0.0001 (MIP-1β), p = 0.002 (TNF-α), p = 0.02 (IFN-γ)] (D) T cells were calculated for each cytokine and plotted with the SE represented with error bars. (E and F) The maximum concentration of each cytokine released for the CAR was calculated relative to the respective maximum concentration for the TCR. Values were adjusted to account for differences in transduction efficiency between TCR and CAR. The average ratios from three separate experiments with CD8 T cells (p = 0.5 for IL-2 versus IL-6, p = 0.9 for IL-2 versus IL-10, p = 0.9 for IL-2 versus TNF-α, p = 0.7 for IL-2 versus IFN-γ, p = 0.05 for IL-6 versus IL-10, p = 0.1 for IL-6 versus TNF-α, p = 0.1 for IL-6 versus IFN-γ, p = 0.9 for IL-10 versus TNF-α, p = 0.9 for IL-10 versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ). For MIP-1β, n = 1 due to saturation at high ligand concentrations (E) and five separate experiments with CD4 T cells (p = 0.07 for IL-2 versus IL-6, p = 0.9 for IL-2 versus IL-10, p = 0.9 for IL-2 versus MIP-1β, p = 0.9 for IL-2 versus TNF-α, p = 0.9 for IL-2 versus IFN-γ, p = 0.07 for IL-6 versus IL-10, p = 0.03 for IL-6 versus MIP-1β, p = 0.007 for IL-6 versus TNF-α, p = 0.02 for IL-6 versus IFN-γ, p = 0.9 for IL-10 versus MIP-1β, p = 0.9 for IL-10 versus TNF-α, p = 0.9 for IL-10 versus IFN-γ, p = 0.9 for MIP-1β versus TNF-α, p = 0.9 for MIP-1β versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ) (F) are plotted with error bars representing the SE. The asterisk (*) indicates statistical significance (p < 0.05) determined using Student t test (EC50) or one-way ANOVA followed by Tukey test (maximum cytokine ratios) in GraphPad Prism 6. The p values generated from the Tukey test are adjusted for multiple comparisons.

Close modal

To test whether CAR activation leads to the same cytokine milieu as T cell activation by a normal TCR, we compared not only the EC50 values, but the maximum amount of cytokine released by T cells expressing the CAR and TCR constructs (Fig. 4E, 4F). In this approach, maximal cytokine values were adjusted to account for differences in transduction efficiency between the TCR and CAR, and the different cytokines serve as internal controls for differences in transduction efficiencies. The CAR secreted ∼2-fold more IL-6 and 1.5-fold more IL-2 at higher ligand concentrations in both CD8 and CD4 T cells, than the TCR. Similar trends were observed in the T1 system in CD4 T cells, with higher concentrations of IL-2 and IL-6 secreted using the CAR compared with the TCR (Supplemental Fig. 1E).

It is possible that the decreased sensitivity of the CAR relative to the TCR could be due in part to the distance of the CD3ζ domain from the transmembrane region, in the second-generation CAR (CD28 followed by CD3ζ). To examine this, we generated a first-generation CAR for D13.1.1, which lacks the intracellular CD28 domain and contains only a membrane-proximal CD3ζ domain (D13.1.1 CD3ζ CAR). We transduced CD4 cells with the D13.1.1 TCR, CAR (CD28/CD3ζ), and CD3ζ CAR. Transduced cells were stained with WT1/HLA-A2 tetramer (Fig. 5A) and stimulated with WT1 peptide in the presence of T2 cells, and supernatants were analyzed for a panel of cytokines using the Luminex multiplex system as described above. We compared the EC50 (Fig. 5B) and maximum cytokine release values (Fig. 5C) between the D13.1.1 TCR, CAR, and CD3ζ CAR (dose-response curves for each cytokine are shown in Supplemental Fig. 2B). The sensitivity of the two CARs was similar for each cytokine, indicating that the decreased sensitivity of the second-generation D13.1.1 CAR relative to the TCR is not due to the inclusion of the intracellular CD28 domain in the CAR construct. We compared the maximal cytokine secretion values between the D13.1.1 TCR and CAR and between the D13.1.1 TCR and CD3ζ CAR (Fig. 5C), and found no statistically significant differences between the two sets of ratios, although the increased IL-6 secretion stimulated by the D13.1.1 CAR relative to the TCR was not recapitulated by the CD3ζ CAR.

FIGURE 5.

Flow cytometry and activity analysis of D13.1.1 TCR, CAR-CD28/CD3ζ, and CAR-CD3ζ constructs transduced in primary CD4 T cells. (A) CD4 T cells were isolated from AAD mice, activated in vitro with anti-CD3/CD28 beads, and transduced with D13.1.1 TCR, CAR-CD28/CD3ζ, and CD3ζ CAR constructs. Transduced cells were stained with 50 nM WT1/HLA-A2 tetramer (mean fluorescence intensity and CV data shown in Supplemental Fig. 2). (B and C) Transduced AAD CD4 T cells were incubated with T2 cells (HLA-A2+) at a 1:1 ratio and various concentrations of WT1 peptide. Supernatants were assayed for IL-2, IL-6, IL-10, MIP-1β, TNF-α, and IFN-γ concentrations using the Luminex Multiplex system (data shown in Supplemental Fig. 2). (B) EC50 values from two separate experiments were calculated for each cytokine and plotted with the SE represented with error bars. (C) The maximum concentrations of each cytokine released for the CAR-CD28/CD3ζ and CD3ζ CAR were calculated relative to the respective maximum concentration for the TCR. The average ratios from two separate experiments are plotted with error bars representing the SE (for TCR versus CAR-CD28/CD3ζ ratios: p = 0.4 for IL-2 versus IL-6, p = 0.9 for IL-2 versus IL-10, p = 0.9 for IL-2 versus MIP-1β, p = 0.9 for IL-2 versus TNF-α, p = 0.9 for IL-2 versus IFN-γ, p = 0.4 for IL-6 versus IL-10, p = 0.3 for IL-6 versus MIP-1β, p = 0.3 for IL-6 versus TNF-α, p = 0.3 for IL-6 versus IFN-γ, p = 0.9 for IL-10 versus MIP-1β, p = 0.9 for IL-10 versus TNF-α, p = 0.9 for IL-10 versus IFN-γ, p = 0.9 for MIP-1β versus TNF-α, p = 0.9 for MIP-1β versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ; for TCR versus CAR- CD3ζ ratios: p = 0.9 for IL-2 versus IL-6, p = 0.3 for IL-2 versus IL-10, p = 0.9 for IL-2 versus MIP-1β, p = 0.9 for IL-2 versus TNF-α, p = 0.9 for IL-2 versus IFN-γ, p = 0.6 for IL-6 versus IL-10, p = 0.9 for IL-6 versus MIP-1β, p = 0.8 for IL-6 versus TNF-α, p = 0.9 for IL-6 versus IFN-γ, p = 0.5 for IL-10 versus MIP-1β, p = 0.2 for IL-10 versus TNF-α, p = 0.4 for IL-10 versus IFN-γ, p = 0.9 for MIP-1β versus TNF-α, p = 0.9 for MIP-1β versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ). Note that the EC50 and maximum cytokine concentrations for the D13.1.1 TCR and CAR-CD28/CD3ζ in these experiments are also included in the average EC50 and maximum cytokine concentrations for these constructs in Fig. 4. The asterisk (*) indicates statistical significance (p < 0.05) determined using one-way ANOVA followed by Tukey test (maximum cytokine ratios) in GraphPad Prism 6. The p values generated from Tukey test are adjusted for multiple comparisons.

FIGURE 5.

Flow cytometry and activity analysis of D13.1.1 TCR, CAR-CD28/CD3ζ, and CAR-CD3ζ constructs transduced in primary CD4 T cells. (A) CD4 T cells were isolated from AAD mice, activated in vitro with anti-CD3/CD28 beads, and transduced with D13.1.1 TCR, CAR-CD28/CD3ζ, and CD3ζ CAR constructs. Transduced cells were stained with 50 nM WT1/HLA-A2 tetramer (mean fluorescence intensity and CV data shown in Supplemental Fig. 2). (B and C) Transduced AAD CD4 T cells were incubated with T2 cells (HLA-A2+) at a 1:1 ratio and various concentrations of WT1 peptide. Supernatants were assayed for IL-2, IL-6, IL-10, MIP-1β, TNF-α, and IFN-γ concentrations using the Luminex Multiplex system (data shown in Supplemental Fig. 2). (B) EC50 values from two separate experiments were calculated for each cytokine and plotted with the SE represented with error bars. (C) The maximum concentrations of each cytokine released for the CAR-CD28/CD3ζ and CD3ζ CAR were calculated relative to the respective maximum concentration for the TCR. The average ratios from two separate experiments are plotted with error bars representing the SE (for TCR versus CAR-CD28/CD3ζ ratios: p = 0.4 for IL-2 versus IL-6, p = 0.9 for IL-2 versus IL-10, p = 0.9 for IL-2 versus MIP-1β, p = 0.9 for IL-2 versus TNF-α, p = 0.9 for IL-2 versus IFN-γ, p = 0.4 for IL-6 versus IL-10, p = 0.3 for IL-6 versus MIP-1β, p = 0.3 for IL-6 versus TNF-α, p = 0.3 for IL-6 versus IFN-γ, p = 0.9 for IL-10 versus MIP-1β, p = 0.9 for IL-10 versus TNF-α, p = 0.9 for IL-10 versus IFN-γ, p = 0.9 for MIP-1β versus TNF-α, p = 0.9 for MIP-1β versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ; for TCR versus CAR- CD3ζ ratios: p = 0.9 for IL-2 versus IL-6, p = 0.3 for IL-2 versus IL-10, p = 0.9 for IL-2 versus MIP-1β, p = 0.9 for IL-2 versus TNF-α, p = 0.9 for IL-2 versus IFN-γ, p = 0.6 for IL-6 versus IL-10, p = 0.9 for IL-6 versus MIP-1β, p = 0.8 for IL-6 versus TNF-α, p = 0.9 for IL-6 versus IFN-γ, p = 0.5 for IL-10 versus MIP-1β, p = 0.2 for IL-10 versus TNF-α, p = 0.4 for IL-10 versus IFN-γ, p = 0.9 for MIP-1β versus TNF-α, p = 0.9 for MIP-1β versus IFN-γ, p = 0.9 for TNF-α versus IFN-γ). Note that the EC50 and maximum cytokine concentrations for the D13.1.1 TCR and CAR-CD28/CD3ζ in these experiments are also included in the average EC50 and maximum cytokine concentrations for these constructs in Fig. 4. The asterisk (*) indicates statistical significance (p < 0.05) determined using one-way ANOVA followed by Tukey test (maximum cytokine ratios) in GraphPad Prism 6. The p values generated from Tukey test are adjusted for multiple comparisons.

Close modal

To understand these findings from a mechanistic perspective, we formulated a mathematical model based on previous approaches examining TCR-mediated signaling (4144). The model (Fig. 6A) involves the receptor in binding equilibrium with the ligand, with kinetic constants (kon and koff) that are presumed to be identical in the TCR and CAR systems in this study. The receptor-ligand complex is denoted as C0 and C1 when unphosphorylated and phosphorylated, respectively. The rate of receptor phosphorylation is given by kp. The downstream Kact represents the ability of the activated receptors to activate downstream signaling by formation of the product, P (e.g., its ability to induce phosphorylation of LAT).

FIGURE 6.

Model of ligand binding and signaling by TCR and CAR constructs. (A) Schematic of the mathematical model. The receptor (R) binds to its ligand (L) with the indicated rate constants to form a complex (C0) that can be phosphorylated with the kp to form a phosphorylated active receptor (C1). The downstream Kact represents the ability of the activated receptor to activate downstream signaling by formation of active product, P (e.g., its ability to induce phosphorylation of LAT). (B) Calculations showing the effect of variation of receptor expression level, kp and Kact on the sensitivity of the cells to Ag. (C) Calculated dose-response curves for a 10-fold higher CAR expression compared with TCR (left) showing that both lower kp (center) or Kact (right) can explain the lower sensitivity of the CAR. (D) An extended model that includes an incoherent feedforward loop can explain the observed bell-shaped dose-response curves. Calculations show that lower values of kp (center) can explain the lower sensitivity of the CAR in this model, whereas the response is completely lost with a lower Kact (right).

FIGURE 6.

Model of ligand binding and signaling by TCR and CAR constructs. (A) Schematic of the mathematical model. The receptor (R) binds to its ligand (L) with the indicated rate constants to form a complex (C0) that can be phosphorylated with the kp to form a phosphorylated active receptor (C1). The downstream Kact represents the ability of the activated receptor to activate downstream signaling by formation of active product, P (e.g., its ability to induce phosphorylation of LAT). (B) Calculations showing the effect of variation of receptor expression level, kp and Kact on the sensitivity of the cells to Ag. (C) Calculated dose-response curves for a 10-fold higher CAR expression compared with TCR (left) showing that both lower kp (center) or Kact (right) can explain the lower sensitivity of the CAR. (D) An extended model that includes an incoherent feedforward loop can explain the observed bell-shaped dose-response curves. Calculations show that lower values of kp (center) can explain the lower sensitivity of the CAR in this model, whereas the response is completely lost with a lower Kact (right).

Close modal

It is possible to simulate the effect of differing receptor concentrations (all other parameters being equal) on the downstream signaling components (P). According to this analysis (Fig. 6B, left), in the 58−/− system where the CAR was expressed at ∼10-fold higher surface levels, the CAR-expressing cells would be expected to have significantly greater sensitivity than the TCR-expressing cells if proximal and downstream phosphorylation events were similar. It follows that either the kp or the Kact of the CAR must be reduced to account for reduced sensitivity of the CAR (Fig. 6B, center and right, respectively). If we fix the receptor concentrations at 30,000 molecules per cell for the TCR (45) and 300,000 for the CAR, kp or Kact need to be reduced by 100-fold (Fig. 6C) to decrease CAR potency by 100-fold (as observed experimentally). In primary cells, where both receptors were expressed at similar levels, the values of kp and Kact would also need to be reduced but by a lower amount to account for the observed differences in sensitivity, because higher expression of the CAR does not need to be overcome.

We also noted that peptide titrations, representing increasing Ag densities, often yielded bell-shaped curves as observed in studies with TCRs (43) and CARs (46). The bell-shaped curves were in general seen with both TCRs and CARs, as long as the latter were able to be titrated at sufficiently high peptide concentrations beyond the peak cytokine levels. We have recently developed a pathway model for cellular signaling that is able to explain this effect based on a large TCR dataset, which appears to be applicable to the CAR format. The model couples an incoherent feedforward loop to kinetic proofreading to explain bell-shaped dose-response curves (Fig. 6D, left). In this model architecture, we find that reduced sensitivity by the CAR may involve a reduction in the kp rather than the Kact (Fig. 6D, center and right, respectively).

To effectively compare TCR and CAR sensitivities, we used the yeast display platform to engineer a high-affinity TCR that bound to WT1/HLA-A2 with nanomolar affinity. Recent Ab engineering efforts isolated a TCR-like Ab specific for the WT1/HLA-A2 complex, which bound with low nanomolar affinity (18). It was observed that in addition to binding to WT1/HLA-A2, this Ab also bound to an HLA-A2 complex containing the PIGQ peptide, which shared similar residues to the WT1 peptide in the N terminus. The high-affinity D13.1.1 TCR did not show binding or activity against the PIGQ/HLA-A2 complex when transduced into CD8 T cells. Based on this result, and the lack of stimulation of CD8 T cells by self-peptide–HLA-A2 complexes, we believe that the high-affinity D13.1.1 TCR provides a more specific reagent than the ESK1 Ab. We have evidence that the greater specificity of the D13.1.1 TCR is likely due to the distributive interactions of its CDR loops with the WT1 peptide, as opposed to the ESK1 Ab that docks only over the N terminus of the WT1 peptide.

To compare the sensitivity of TCRs to CARs, two high-affinity TCRs, one for WT1/HLA-A2 and another MART1/HLA-A2, were formatted as full-length TCRs (variable α and β domains followed by constant domains) as well as CAR constructs (single-chain TCR variable domains tethered to intracellular CD28 and CD3ζ signaling domains). The TCR/CAR systems described in this study allow quantitative comparisons of signaling outcomes and sensitivities, because the recognition and binding properties of the receptors are identical. In the murine 58−/− T cell hybridoma cell line, the lower expression of the TCR, compared with the CAR, may be due to the stoichiometric levels of CD3 subunits, which are limiting and thus control surface levels of the entire TCR/CD3 complex (47). CAR expression is not known to be dependent on coexpression of CD3 subunits and thus total cell surface levels may be controlled by transcriptional or other mechanisms.

In primary CD4 and CD8 T cells, the expression of conventional TCRs was more consistent between individual cells, whereas CARs were expressed at a broader range of receptor levels. More homogenous expression for the TCR could be due to a dependence on CD3 subunit expression levels and assembly. Because CARs do not require CD3 coexpression, their expression levels are likely more dependent on the site of vector integration. Methods to generate site-directed integrations of CAR constructs will likely lead to a more consistent surface level expression of CARs (14, 48). Techniques that are not dependent on genome integration, such as RNA electroporation, may also yield more consistent expression levels of CARs. It is not yet clear if T cells expressing higher or lower levels of CARs will be optimal for driving T cell activation, but the answer may depend on Ag levels on tumors.

The enhanced sensitivity for pepHLA-A2 exhibited by the full-length TCR in both the T cell hybridoma cell line and primary CD4 T cells, is likely due to the robust CD3-based signaling machinery that assembles with a TCR as compared with a CAR construct. That is, a fully assembled TCR complex contains 10 ITAMs with 20 tyrosine residues available for phosphorylation, compared with the typical CD28/CD3ζ-based CAR construct, which has only 3 ITAMS and 6 tyrosine residues (10). As CARs can potentially form dimers, this would increase the number of ITAMs from three to six, with a total of 12 tyrosine residues available for phosphorylation. Although still less than a single TCR/CD3 complex, this might suggest that other factors also play a role in the reduced sensitivity of CARs.

Studies have shown that some CARs have enhanced sensitivity when the extracellular spacer domain is optimized (4951). How this spacer provides enhanced sensitivity has yet to be determined, however, it is possible that the spacer domain provides greater flexibility or size for the scFv to optimally engage its cell surface ligand. The distance between T cell and target cell membranes influences which costimulatory and inhibitory molecules are recruited to the immunological synapse. The size of the interacting receptor-ligand pairs could influence the ability to exclude, by a segregation mechanism, inhibitory signaling molecules such as CD45. Previous work studying the signaling mechanisms of TCRs and a typical scFv-CAR showed that signaling through both receptors involved efficient CD45 exclusion (52, 53). The dimensions of our TCR and CAR constructs are the same as in their study, and it would seem likely that addition of larger extracellular domains to our CAR would, if anything, decrease sensitivity as the construct would have dimensions that were closer to CD45 and thus reduce the level of segregation. Nevertheless, the CAR constructs used in this study provide a simple approach to exploring how to optimize both extracellular and intracellular domains, in a comparative approach to the natural TCR/CD3 system.

Using a validated mathematical T cell signaling model, our primary hypothesis is that the CAR (CD28/CD3ζ form) takes longer than the TCR complex to achieve a fully activated phosphorylated state or is less effective at phosphorylating downstream proteins (or a combination of both). Both could be explained by having fewer phosphorylation sites, as is the case when comparing the natural CD3 complex with the signaling domains of the CAR. It is important to note that at the affinities studied, these outcomes are observed even in the absence of the CD4 or CD8 coreceptors that are well known to further enhance sensitivity of TCR-mediating signaling.

The enhanced sensitivity of the TCR/CD3 complex compared with the CAR constructs suggests that targeting pepHLA in adoptive T cell therapies with a CAR will require higher expression levels by the cancer cell. This may provide a useful safety margin when targeting pepHLA complexes expressed at low levels in normal tissue and higher levels in malignant tissue. However, when targeting pepHLA complexes that have limited expression by the cancer cells (e.g., <50 complexes per cell), a normal TCR will likely provide the requisite sensitivity.

The observation that at higher Ag densities the CAR mediated maximal release of cytokines differentially (e.g., higher levels of IL-6 but lower levels of IL-10) suggests a different balance of signaling pathway activation in CARs as compared with TCRs. IL-6 is an acute proinflammatory cytokine that utilizes JAK/STAT signaling (54) and it is now well known that CAR-mediated therapies against CD19 have shown cytokine release syndrome with high levels of IL-6 in some patients (5557). To further determine which components of the CAR construct conferred this proinflammatory phenotype, a first-generation CAR containing only the CD3ζ domain was tested. Although this first-generation CAR shared a similar sensitivity as the CD28/CD3ζ CAR, it did not mediate the same enhanced level of IL-6 at high Ag density. Our results suggest that the signaling machinery used in the CD28-CD3ζ CAR construct may be biased toward a more inflammatory response under conditions of high Ag levels, compared with conventional TCRs. It may be important to consider the range of Ag levels observed among cancers and to engineer scFv and signaling domains that address these issues.

The exact mechanism of T cell signaling, either by a TCR or CAR, has yet to be fully elucidated. Two hypotheses regarding TCR signaling have involved either conformational changes propagated through the membrane (58) or kinetic proofreading (41). It has also been suggested that TCRs and other highly sensitive receptors discriminate ligands through the accumulation of catch bonds, which deliver additional force to the interaction (59, 60). Given that our system utilizes the same Ag-binding domains, the differences in sensitivity observed between TCR and CAR are unlikely due to a difference in catch bond potential.

In titrations of the Ag peptide, with both TCR and CAR systems, we also observed a decrease in the level of cytokines released at high ligand concentrations. Previous models have shown that the behaviors associated with such curves, at high Ag density, are likely the result of a negative feedback mechanism involving SHP-1 (39, 40). The similar high-concentration response profiles for both TCRs and CARs used in this study support the idea that CARs, like TCRs, are subject to both positive signals through the MAPK pathways and negative signals through SHP-1 and other regulatory molecules. These observations can be more difficult to see in typical CAR systems, where Ag density above the optimal cytokine release values may not be achievable, or because full Ag titrations are not conducted.

In summary, the TCR/CAR system described in this study provides a rapid strategy to explore Ag densities by simply titrating the antigenic peptides into the target cells that express the appropriate MHC (HLA-A2 in our case). Although it is unlikely that the two signaling domains within the CAR construct tested in this study can fully recapitulate a conventional TCR/CD3-induced T cell response, there are numerous efforts to examine alternative CAR constructs (1, 8, 9, 12). It is possible that including regulatory domains with or without additional stimulatory domains may be beneficial in balancing the CAR cytokine response. Regardless, CARs will likely also have to be optimized based on the receptor’s affinity and the intended target’s expression level on the cancer cell surface.

We thank Barbara Pilas for assistance with flow cytometry. We thank Gregoire Altan-Bonnet for helpful discussions about negative feedback at high levels of antigen.

This work was supported by National Institutes of Health Grants 1R01 CA178844, CA187592, and CA037156 to D.M.K., National Institutes of Health National Research Service Award CA180723 to D.T.H., National Institutes of Health Training Grant T32 GM070421 to S.N.S., and a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant 098363) to O.D.

The online version of this article contains supplemental material.

Abbreviations used in this article:

CAR

chimeric Ag receptor

CV

coefficient of variation

HA

hemagglutinin

Kact

activation rate

kp

kinetic proofreading rate

pepMHC

peptide MHC

scFv

single-chain fragment variable

SHP-1

Src homology 2 domain phosphatase-1.

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D.M.K., D.T.H., and S.N.S. are inventors on various patents licensed by the University of Illinois to commercial entities. J.D.S. is an employee of AbbVie. P.D.G. is a cofounder of Juno Therapeutics. The other authors have no financial conflicts of interest.

Supplementary data